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I am unable to google something useful on this subject, so I'd appreciate either links to articles that deal in this subject, or direct answers here, either is fine.
I am implementing a search system in PHP/MySQL on a site that has quite a lot of visitors, so I am going to implement some restrictions to the length of the characters a visitor is allowed to enter in the search field and the minimum time required between two searches. Since I'm kind of new to these problems and I don't really know the "real reasons" why this is usually done, it's only my assumptions that the character minimum length is implemented to minimize the number of results the database will return, and the time between searches is implemented to prevent robots from spamming the search system and slowing down the site. Is that right?
And finally, the question of how to implement the minimum time between two searches. The solution i came up with, in pseudo-code, is this
Set a test cookie at the URL where the search form is submitted to
Redirect user to the URL where the search results should be output
Check if the test cookie exists
If not, output a warning that he isn't allowed to use the search system (is probably a robot)
Check if a cookie exists that tells the time of the last search
If this was less that 5 seconds ago, output a warning that he should wait before searching again
Search
Set a cookie with the time of last search to current time
Output search results
Is this the best way to do it?
I understand this means visitors that have cookies disabled will not be able to use the search system, but is that really a problem these days? I couldn't find the statistics for 2012, but I managed to find data saying 3.7% of people had disabled cookies in 2009. That doesn't seem like a lot and I suppose should probably be even less these days.
"only my assumptions that the character minimum length is implemented to minimize the number of results the database will return". Your assumption is absolutely correct. It reduces the number of potential results, by forcing the user to think about, what it is they wish to search.
As far as bots spamming your search, you could implement a captcha, the most frequently used is recaptcha. If you don't want to show a captcha right away, you can track (via session) the number of times the user submitted search, and if X amount of searches occur within a certain time frame, then render the captcha.
I've seen sites like SO and thechive.com implement this type of strategy, where captcha isn't rendered right away, but will be rendered if a threshold is encountered.
This way you're preventing Search Engine from indexing your search results. A cleaner way of doing this would be:
Get IP where search originated
Store that IP in a cache system such as memcached and the time that query was made
If another query is sent from same IP and less then x second passed simply reject it or make the user wait
Another thing you can do to increase performance is to take a look at analytics and see which queries are made most often and cache those so when a request comes in you serve the cached version and not make a full db query, parsing, etc...
Another naive option would be to have a script run 1-2 times a day running all common queries and create static HTML files that users hit when making particular search queries instead of hitting the db.
Many of us need to deal with user input, search queries, and situations where the input text can potentially contain profanity or undesirable language. Oftentimes this needs to be filtered out.
Where can one find a good list of swear words in various languages and dialects?
Are there APIs available to sources that contain good lists? Or maybe an API that simply says "yes this is clean" or "no this is dirty" with some parameters?
What are some good methods for catching folks trying to trick the system, like a$$, azz, or a55?
Bonus points if you offer solutions for PHP. :)
Edit: Response to answers that say simply avoid the programmatic issue:
I think there is a place for this kind of filter when, for instance, a user can use public image search to find pictures that get added to a sensitive community pool. If they can search for "penis", then they will likely get many pictures of, yep. If we don't want pictures of that, then preventing the word as a search term is a good gatekeeper, though admittedly not a foolproof method. Getting the list of words in the first place is the real question.
So I'm really referring to a way to figure out of a single token is dirty or not and then simply disallow it. I'd not bother preventing a sentiment like the totally hilarious "long necked giraffe" reference. Nothing you can do there. :)
Obscenity Filters: Bad Idea, or Incredibly Intercoursing Bad Idea?
Also, one can't forget The Untold History of Toontown's SpeedChat, where even using a "safe-word whitelist" resulted in a 14-year-old quickly circumventing it with:
"I want to stick my long-necked Giraffe up your fluffy white bunny."
Bottom line: Ultimately, for any system that you implement, there is absolutely no substitute for human review (whether peer or otherwise). Feel free to implement a rudimentary tool to get rid of the drive-by's, but for the determined troll, you absolutely must have a non-algorithm-based approach.
A system that removes anonymity and introduces accountability (something that Stack Overflow does well) is helpful also, particularly in order to help combat John Gabriel's G.I.F.T.
You also asked where you can get profanity lists to get you started -- one open-source project to check out is Dansguardian -- check out the source code for their default profanity lists. There is also an additional third party Phrase List that you can download for the proxy that may be a helpful gleaning point for you.
Edit in response to the question edit: Thanks for the clarification on what you're trying to do. In that case, if you're just trying to do a simple word filter, there are two ways you can do it. One is to create a single long regexp with all of the banned phrases that you want to censor, and merely do a regex find/replace with it. A regex like:
$filterRegex = "(boogers|snot|poop|shucks|argh)"
and run it on your input string using preg_match() to wholesale test for a hit,
or preg_replace() to blank them out.
You can also load those functions up with arrays rather than a single long regex, and for long word lists, it may be more manageable. See the preg_replace() for some good examples as to how arrays can be used flexibly.
For additional PHP programming examples, see this page for a somewhat advanced generic class for word filtering that *'s out the center letters from censored words, and this previous Stack Overflow question that also has a PHP example (the main valuable part in there is the SQL-based filtered word approach -- the leet-speak compensator can be dispensed with if you find it unnecessary).
You also added: "Getting the list of words in the first place is the real question." -- in addition to some of the previous Dansgaurdian links, you may find this handy .zip of 458 words to be helpful.
Whilst I know that this question is fairly old, but it's a commonly occurring question...
There is both a reason and a distinct need for profanity filters (see Wikipedia entry here), but they often fall short of being 100% accurate for very distinct reasons; Context and accuracy.
It depends (wholly) on what you're trying to achieve - at it's most basic, you're probably trying to cover the "seven dirty words" and then some... Some businesses need to filter the most basic of profanity: basic swear words, URLs or even personal information and so on, but others need to prevent illicit account naming (Xbox live is an example) or far more...
User generated content doesn't just contain potential swear words, it can also contain offensive references to:
Sexual acts
Sexual orientation
Religion
Ethnicity
Etc...
And potentially, in multiple languages. Shutterstock has developed basic dirty-words lists in 10 languages to date, but it's still basic and very much oriented towards their 'tagging' needs. There are a number of other lists available on the web.
I agree with the accepted answer that it's not a defined science and as language is a continually evolving challenge but one where a 90% catch rate is better than 0%. It depends purely on your goals - what you're trying to achieve, the level of support you have and how important it is to remove profanities of different types.
In building a filter, you need to consider the following elements and how they relate to your project:
Words/phrases
Acronyms (FOAD/LMFAO etc)
False positives (words, places and names like 'mishit', 'scunthorpe' and 'titsworth')
URLs (porn sites are an obvious target)
Personal information (email, address, phone etc - if applicable)
Language choice (usually English by default)
Moderation (how, if at all, you can interact with user generated content and what you can do with it)
You can easily build a profanity filter that captures 90%+ of profanities, but you'll never hit 100%. It's just not possible. The closer you want to get to 100%, the harder it becomes... Having built a complex profanity engine in the past that dealt with more than 500K realtime messages per day, I'd offer the following advice:
A basic filter would involve:
Building a list of applicable profanities
Developing a method of dealing with derivations of profanities
A moderately complex filer would involve, (In addition to a basic filter):
Using complex pattern matching to deal with extended derivations (using advanced regex)
Dealing with Leetspeak (l33t)
Dealing with false positives
A complex filter would involve a number of the following (In addition to a moderate filter):
Whitelists and blacklists
Naive bayesian inference filtering of phrases/terms
Soundex functions (where a word sounds like another)
Levenshtein distance
Stemming
Human moderators to help guide a filtering engine to learn by example or where matches aren't accurate enough without guidance (a self/continually-improving system)
Perhaps some form of AI engine
I don't know of any good libraries for this, but whatever you do, make sure that you err in the direction of letting stuff through. I've dealt with systems that wouldn't allow me to use "mpassell" as a username, because it contains "ass" as a substring. That's a great way to alienate users!
During a job interview of mine, the company CTO who was interviewing me tried out a word/web game I wrote in Java. Out of a word list of the entire Oxford English dictionary, what was the first word that came up to be guessed?
Of course, the most foul word in the English language.
Somehow, I still got the job offer, but I then tracked down a profanity word list (not unlike this one) and wrote a quick script to generate a new dictionary without all of the bad words (without even having to look at the list).
For your particular case, I think comparing the search to real words sounds like the way to go with a word list like that. The alternative styles/punctuation require a bit more work, but I doubt users will use that often enough to be an issue.
a profanity filtering system will never be perfect, even if the programmer is cocksure and keeps abreast of all nude developments
that said, any list of 'naughty words' is likely to perform as well as any other list, since the underlying problem is language understanding which is pretty much intractable with current technology
so, the only practical solution is twofold:
be prepared to update your dictionary frequently
hire a human editor to correct false positives (e.g. "clbuttic" instead of "classic") and false negatives (oops! missed one!)
The only way to prevent offensive user input is to prevent all user input.
If you insist on allowing user input and need moderation, then incorporate human moderators.
Have a look at CDYNE's Profanity Filter Web Service
Testing URL
Beware of localization issues: what is a swearword in one language might be a perfectly normal word in another.
One current example of this: ebay uses a dictionary approach to filter "bad words" from feedback. If you try to enter the german translation of "this was a perfect transaction" ("das war eine perfekte Transaktion"), ebay will reject the feedback due to bad words.
Why? Because the german word for "was" is "war", and "war" is in ebay dictionary of "bad words".
So beware of localisation issues.
Regarding your "trick the system" subquestion, you can handle that by normalizing both the "bad word" list and the user-entered text before doing your search. e.g., Use a series of regexes (or tr if PHP has it) to convert [z$5] to "s", [4#] to "a", etc., then compare the normalized "bad word" list against the normalized text. Note that the normalization could potentially lead to additional false positives, although I can't think of any actual cases at the moment.
The larger challenge is to come up with something that will let people quote "The pen is mightier than the sword" while blocking "p e n i s".
I collected 2200 bad words in 12 languages: en, ar, cs, da, de, eo, es, fa, fi, fr, hi, hu, it, ja, ko, nl, no, pl, pt, ru, sv, th, tlh, tr, zh.
MySQL dump, JSON, XML or CSV options are available.
https://github.com/turalus/openDB
I'd suggest you to execute this SQL into your DB and check everytime when user inputs something.
If you can do something like Digg/Stackoverflow where the users can downvote/mark obscene content... do so.
Then all you need to do is review the "naughty" users, and block them if they break the rules.
I'm a little late to the party, but I have a solution that might work for some who read this. It's in javascript instead of php, but there's a valid reason for it.
Full disclosure, I wrote this plugin...
Anyways.
The approach I've gone with is to allow a user to "Opt-In" to their profanity filtering. Basically profanity will be allowed by default, but if my users don't want to read it, they don't have to. This also helps with the "l33t sp3#k" issue.
The concept is a simple jquery plugin that gets injected by the server if the client's account is enabling profanity filtering. From there, it's just a couple simple lines that blot out the swears.
Here's the demo page
https://chaseflorell.github.io/jQuery.ProfanityFilter/demo/
<div id="foo">
ass will fail but password will not
</div>
<script>
// code:
$('#foo').profanityFilter({
customSwears: ['ass']
});
</script>
result
*** will fail but password will not
Also late in the game, but doing some researches and stumbled across here. As others have mentioned, it's just almost close to impossible if it was automated, but if your design/requirement can involve in some cases (but not all the time) human interactions to review whether it is profane or not, you may consider ML. https://learn.microsoft.com/en-us/azure/cognitive-services/content-moderator/text-moderation-api#profanity is my current choice right now for multiple reasons:
Supports many localization
They keep updating the database, so I don't have to keep up with latest slangs or languages (maintenance issue)
When there is a high probability (I.e. 90% or more) you can just deny it pragmatically
You can observe for category which causes a flag that may or may not be profanity, and can have somebody review it to teach that it is or isn't profane.
For my need, it was/is based on public-friendly commercial service (OK, videogames) which other users may/will see the username, but the design requires that it has to go through profanity filter to reject offensive username. The sad part about this is the classic "clbuttic" issue will most likely occur since usernames are usually single word (up to N characters) of sometimes multiple words concatenated... Again, Microsoft's cognitive service will not flag "Assist" as Text.HasProfanity=true but may flag one of the categories probability to be high.
As the OP inquires, what about "a$$", here's a result when I passed it through the filter:, as you can see, it has determined it's not profane, but it has high probability that it is, so flags as recommendations of reviewing (human interactions).
When probability is high, I can either return back "I'm sorry, that name is already taken" (even if it isn't) so that it is less offensive to anti-censorship persons or something, if we don't want to integrate human review, or return "Your username have been notified to the live operation department, you may wait for your username to be reviewed and approved or chose another username". Or whatever...
By the way, the cost/price for this service is quite low for my purpose (how often does the username gets changed?), but again, for OP maybe the design demands more intensive queries and may not be ideal to pay/subscribe for ML-services, or cannot have human-review/interactions. It all depends on the design... But if design does fit the bill, perhaps this can be OP's solution.
If interested, I can list the cons in the comment in the future.
Once you have a good MYSQL table of some bad words you want to filter (I started with one of the links in this thread), you can do something like this:
$errors = array(); //Initialize error array (I use this with all my PHP form validations)
$SCREENNAME = mysql_real_escape_string($_POST['SCREENNAME']); //Escape the input data to prevent SQL injection when you query the profanity table.
$ProfanityCheckString = strtoupper($SCREENNAME); //Make the input string uppercase (so that 'BaDwOrD' is the same as 'BADWORD'). All your values in the profanity table will need to be UPPERCASE for this to work.
$ProfanityCheckString = preg_replace('/[_-]/','',$ProfanityCheckString); //I allow alphanumeric, underscores, and dashes...nothing else (I control this with PHP form validation). Pull out non-alphanumeric characters so 'B-A-D-W-O-R-D' shows up as 'BADWORD'.
$ProfanityCheckString = preg_replace('/1/','I',$ProfanityCheckString); //Replace common numeric representations of letters so '84DW0RD' shows up as 'BADWORD'.
$ProfanityCheckString = preg_replace('/3/','E',$ProfanityCheckString);
$ProfanityCheckString = preg_replace('/4/','A',$ProfanityCheckString);
$ProfanityCheckString = preg_replace('/5/','S',$ProfanityCheckString);
$ProfanityCheckString = preg_replace('/6/','G',$ProfanityCheckString);
$ProfanityCheckString = preg_replace('/7/','T',$ProfanityCheckString);
$ProfanityCheckString = preg_replace('/8/','B',$ProfanityCheckString);
$ProfanityCheckString = preg_replace('/0/','O',$ProfanityCheckString); //Replace ZERO's with O's (Capital letter o's).
$ProfanityCheckString = preg_replace('/Z/','S',$ProfanityCheckString); //Replace Z's with S's, another common substitution. Make sure you replace Z's with S's in your profanity database for this to work properly. Same with all the numbers too--having S3X7 in your database won't work, since this code would render that string as 'SEXY'. The profanity table should have the "rendered" version of the bad words.
$CheckProfanity = mysql_query("SELECT * FROM DATABASE.TABLE p WHERE p.WORD = '".$ProfanityCheckString."'");
if(mysql_num_rows($CheckProfanity) > 0) {$errors[] = 'Please select another Screen Name.';} //Check your profanity table for the scrubbed input. You could get real crazy using LIKE and wildcards, but I only want a simple profanity filter.
if (count($errors) > 0) {foreach($errors as $error) {$errorString .= "<span class='PHPError'>$error</span><br /><br />";} echo $errorString;} //Echo any PHP errors that come out of the validation, including any profanity flagging.
//You can also use these lines to troubleshoot.
//echo $ProfanityCheckString;
//echo "<br />";
//echo mysql_error();
//echo "<br />";
I'm sure there is a more efficient way to do all those replacements, but I'm not smart enough to figure it out (and this seems to work okay, albeit inefficiently).
I believe that you should err on the side of allowing users to register, and use humans to filter and add to your profanity table as required. Though it all depends on the cost of a false positive (okay word flagged as bad) versus a false negative (bad word gets through). That should ultimately govern how aggressive or conservative you are in your filtering strategy.
I would also be very careful if you want to use wildcards, since they can sometimes behave more onerously than you intend.
I agree with HanClinto's post higher up in this discussion. I generally use regular expressions to string-match input text. And this is a vain effort, as, like you originally mentioned you have to explicitly account for every trick form of writing popular on the net in your "blocked" list.
On a side note, while others are debating the ethics of censorship, I must agree that some form is necessary on the web. Some people simply enjoy posting vulgarity because it can be instantly offensive to a large body of people, and requires absolutely no thought on the author's part.
Thank you for the ideas.
HanClinto rules!
Frankly, I'd let them get the "trick the system" words out and ban them instead, which is just me. But it also makes the programming simpler.
What I'd do is implement a regex filter like so: /[\s]dooby (doo?)[\s]/i or it the word is prefixed on others, /[\s]doob(er|ed|est)[\s]/. These would prevent filtering words like assuaged, which is perfectly valid, but would also require knowledge of the other variants and updating the actual filter if you learn a new one. Obviously these are all examples, but you'd have to decide how to do it yourself.
I'm not about to type out all the words I know, not when I don't actually want to know them.
Don't. It just leads to problems. One clbuttic personal experience I have with profanity filters is the time where I was kick/banned from an IRC channel for mentioning that I was "heading over the bridge to Hancock for a couple hours" or something to that effect.
I agree with the futility of the subject, but if you have to have a filter, check out Ning's Boxwood:
Boxwood is a PHP extension for fast replacement of multiple words in a piece of text. It supports case-sensitive and case-insensitive matching. It requires that the text it operates on be encoded as UTF-8.
Also see this blog post for more details:
Fast Multiple String Replacement in PHP
With Boxwood, you can have your list of search terms be as long as you like -- the search and replace algorithm doesn't get slower with more words on the list of words to look for. It works by building a trie of all the search terms and then scans your subject text just once, walking down elements of the trie and comparing them to characters in your text. It supports US-ASCII and UTF-8, case-sensitive or insensitive matching, and has some English-centric word boundary checking logic.
I concluded, in order to create a good profanity filter we need 3 main components, or at least it is what I am going to do. These they are:
The filter: a background service that verify against a blacklist, dictionary or something like that.
Not allow anonymous account
Report abuse
A bonus, it will be to reward somehow those who contribute with accurate abuse reporters and punish the offender, e.g. suspend their accounts.
Don't.
Because:
Clbuttic
Profanity is not OMG EVIL
Profanity cannot be effectively defined
Most people quite probably don't appreciate being "protected" from profanity
Edit: While I agree with the commenter who said "censorship is wrong", that is not the nature of this answer.
I have a PHP/MySQL driven site, which I have not maintained for the past 6 months. It is a site where users come and submit their articles. I have 50.000 articles and by some 'ad hoc' tests I should say that about 50-60% is spam and copy pasted text from other sites.
I am looking to write a PHP script that will take some base parameters to mark/remove spam text(not copy/pasted, for this step only pure spam) so my idea is to make a script which takes every unit, counts characters, words, different words and phrases usage and word density and depending on those factors remove as pure spam (with much repeated phrases, etc.). So for this I will lose a whole day and my question is:
Is there some solution already developed in PHP?
If I need to code it myself, what parameters on determining spam should I use?
Here's a PHP class that I've used in the past - Basic Spam Class
I am not the author, so I don't take any responsibility for potential damage done by the code. I've used it for checking short texts though - user comments on a site, so I'm not sure about the performance on 50k of long articles, maybe you will need to do some enhancements on it. But at least you have something to start from.
Maybe you could take a look at Akismet and Bad Behaviour. The first one to analyze the articles you already have (as well as future ones) and Bad Behaviour to combat spam before it ever gets into your database.
They may not be ideal, but they could help you on your way.
I've observed that a lot of spam posts on sites like that have a lack of articles. They contain just a bunch of keywords and links. You could add a parameter for minimum number of articles. If less than 1% of the post is articles you could reject it as spam.
For example, if you count the number of thes ans as and somes in the above paragraph you get 3 as and 1 the (4 articles total out of 43 words is 9.3%)
I have an online RPG game which I'm taking seriously. Lately I've been having problem with users making bogus characters with bogus names, just a bunch of different letters. Like Ghytjrhfsdjfnsdms, Yiiiedawdmnwe, Hhhhhhhhhhejejekk. I force them to change names but it's becoming too much.
What can I do about this?
Could I somehow check so at least you can't use more than 2 of the same letter beside each other?? And also maybe if it contains vowels
I would recommend concentrating your energy on building a user interface that makes it brain-dead easy to list all new names to an administrator, and a big fat "force to rename" mechanism that minimizes the admin's workload, rather than trying to define the incredibly complex and varied rules that make a name (and program a regular expression to match them!).
Update - one thing comes to mind, though: Second Life used to allow you to freely specify a first name (maybe they check against a database of first names, I don't know) and then gives you a selection of a few hundred pre-defined last names to choose from. For an online RPG, that may already be enough.
You could use a metaphone implementation and then look for "unnatural" patterns:
http://www.php.net/manual/en/function.metaphone.php
This is the PHP function for metaphone string generation. You pass in a string and it returns the phonetic representation of the text. You could, in theory, pass a large number of "human" names and then store a database of valid combinations of phonemes. To test a questionable name, just see if the combinations of phonemes are in the database.
Hope this helps!
Would limiting the amount of consonants or vowels in a row, and preventing repeating help?
As a regex:
if(preg_match('/[bcdfghjklmnpqrtsvwxyz]{4}|[aeiou]{4}|([a-z])\1{2}/i',$name)){
//reject
}
Possibly use iconv with ASCII//TRANSLIT if you allow accentuated characters.
What if you would use the Google Search API to see if the name returns any results?
I say take #Unicron's approach, of easy admin rejection, but on each rejection, add the name to a database of banned names. You might be able to use this data to detect specific attacks generation large numbers of users based on patterns. Will of course be very difficult to detect one-offs.
I had this issue as well. An easy way to solve it is to force user names to validate against a database of world-wide names. Essentially you have a database on the backend with a few hundred thousand first and last names for both genders, and make their name match.
With a little bit of searching on google, you can find many name databases.
Could I somehow check so at least you cant use more than 2 of the same letter beside each other?? and also maybe if it contains vowels
If you just want this, you can do:
preg_match('/(.)\\1\\1/i', $name);
This will return 1 if anything appears three times in a row or more.
This link might help. You might also be able to plug it through a (possibly modified) speech synthesiser engine and analyse how much trouble it's having generating the speech, without actually generating it.
You should try implementing a modified version of a Naive Bayes spam filter. For example, in normal spam detection you calculate the probability of a word being spam and use individual word probabilities to determine if the whole message is spam.
Similarly, you could download a word list, and compute the probability that a pair of letters belongs to a real word.
E.g., create a 26x26 table say, T. Let the 5th row represent the letter e and let entry T(5,1) be the number of times ea appeared in your word list. Once you're done counting, divide each element in each row with the sum of the row so that T(5,1) is now the percentage of times ea appears in your word list in a pair of letter starting with e.
Now, you can use the individual pair probability (e.g. in Jimy that would be {Ji,im,iy} to check whether Jimy is an acceptable name or not. You'll probably have to determine the right probability to threshold at, but try it out --- it's not that hard to implement.
What do you think about delegating the responsibility of creating users to a third party source (like Facebook, Twitter, OpenId...)?
Doing that will not solve your problem, but it will be more work for a user to create additional accounts - which (assuming that the users are lazy, since most are) should discourage the creation of additional "dummy" users.
It seems as though you are going to need a fairly complex preg function. I don't want to take the time to write one for you, as you will learn more writing it yourself, but I will help along the way if you post some attempts.
http://php.net/manual/en/function.preg-match.php
Many of us need to deal with user input, search queries, and situations where the input text can potentially contain profanity or undesirable language. Oftentimes this needs to be filtered out.
Where can one find a good list of swear words in various languages and dialects?
Are there APIs available to sources that contain good lists? Or maybe an API that simply says "yes this is clean" or "no this is dirty" with some parameters?
What are some good methods for catching folks trying to trick the system, like a$$, azz, or a55?
Bonus points if you offer solutions for PHP. :)
Edit: Response to answers that say simply avoid the programmatic issue:
I think there is a place for this kind of filter when, for instance, a user can use public image search to find pictures that get added to a sensitive community pool. If they can search for "penis", then they will likely get many pictures of, yep. If we don't want pictures of that, then preventing the word as a search term is a good gatekeeper, though admittedly not a foolproof method. Getting the list of words in the first place is the real question.
So I'm really referring to a way to figure out of a single token is dirty or not and then simply disallow it. I'd not bother preventing a sentiment like the totally hilarious "long necked giraffe" reference. Nothing you can do there. :)
Obscenity Filters: Bad Idea, or Incredibly Intercoursing Bad Idea?
Also, one can't forget The Untold History of Toontown's SpeedChat, where even using a "safe-word whitelist" resulted in a 14-year-old quickly circumventing it with:
"I want to stick my long-necked Giraffe up your fluffy white bunny."
Bottom line: Ultimately, for any system that you implement, there is absolutely no substitute for human review (whether peer or otherwise). Feel free to implement a rudimentary tool to get rid of the drive-by's, but for the determined troll, you absolutely must have a non-algorithm-based approach.
A system that removes anonymity and introduces accountability (something that Stack Overflow does well) is helpful also, particularly in order to help combat John Gabriel's G.I.F.T.
You also asked where you can get profanity lists to get you started -- one open-source project to check out is Dansguardian -- check out the source code for their default profanity lists. There is also an additional third party Phrase List that you can download for the proxy that may be a helpful gleaning point for you.
Edit in response to the question edit: Thanks for the clarification on what you're trying to do. In that case, if you're just trying to do a simple word filter, there are two ways you can do it. One is to create a single long regexp with all of the banned phrases that you want to censor, and merely do a regex find/replace with it. A regex like:
$filterRegex = "(boogers|snot|poop|shucks|argh)"
and run it on your input string using preg_match() to wholesale test for a hit,
or preg_replace() to blank them out.
You can also load those functions up with arrays rather than a single long regex, and for long word lists, it may be more manageable. See the preg_replace() for some good examples as to how arrays can be used flexibly.
For additional PHP programming examples, see this page for a somewhat advanced generic class for word filtering that *'s out the center letters from censored words, and this previous Stack Overflow question that also has a PHP example (the main valuable part in there is the SQL-based filtered word approach -- the leet-speak compensator can be dispensed with if you find it unnecessary).
You also added: "Getting the list of words in the first place is the real question." -- in addition to some of the previous Dansgaurdian links, you may find this handy .zip of 458 words to be helpful.
Whilst I know that this question is fairly old, but it's a commonly occurring question...
There is both a reason and a distinct need for profanity filters (see Wikipedia entry here), but they often fall short of being 100% accurate for very distinct reasons; Context and accuracy.
It depends (wholly) on what you're trying to achieve - at it's most basic, you're probably trying to cover the "seven dirty words" and then some... Some businesses need to filter the most basic of profanity: basic swear words, URLs or even personal information and so on, but others need to prevent illicit account naming (Xbox live is an example) or far more...
User generated content doesn't just contain potential swear words, it can also contain offensive references to:
Sexual acts
Sexual orientation
Religion
Ethnicity
Etc...
And potentially, in multiple languages. Shutterstock has developed basic dirty-words lists in 10 languages to date, but it's still basic and very much oriented towards their 'tagging' needs. There are a number of other lists available on the web.
I agree with the accepted answer that it's not a defined science and as language is a continually evolving challenge but one where a 90% catch rate is better than 0%. It depends purely on your goals - what you're trying to achieve, the level of support you have and how important it is to remove profanities of different types.
In building a filter, you need to consider the following elements and how they relate to your project:
Words/phrases
Acronyms (FOAD/LMFAO etc)
False positives (words, places and names like 'mishit', 'scunthorpe' and 'titsworth')
URLs (porn sites are an obvious target)
Personal information (email, address, phone etc - if applicable)
Language choice (usually English by default)
Moderation (how, if at all, you can interact with user generated content and what you can do with it)
You can easily build a profanity filter that captures 90%+ of profanities, but you'll never hit 100%. It's just not possible. The closer you want to get to 100%, the harder it becomes... Having built a complex profanity engine in the past that dealt with more than 500K realtime messages per day, I'd offer the following advice:
A basic filter would involve:
Building a list of applicable profanities
Developing a method of dealing with derivations of profanities
A moderately complex filer would involve, (In addition to a basic filter):
Using complex pattern matching to deal with extended derivations (using advanced regex)
Dealing with Leetspeak (l33t)
Dealing with false positives
A complex filter would involve a number of the following (In addition to a moderate filter):
Whitelists and blacklists
Naive bayesian inference filtering of phrases/terms
Soundex functions (where a word sounds like another)
Levenshtein distance
Stemming
Human moderators to help guide a filtering engine to learn by example or where matches aren't accurate enough without guidance (a self/continually-improving system)
Perhaps some form of AI engine
I don't know of any good libraries for this, but whatever you do, make sure that you err in the direction of letting stuff through. I've dealt with systems that wouldn't allow me to use "mpassell" as a username, because it contains "ass" as a substring. That's a great way to alienate users!
During a job interview of mine, the company CTO who was interviewing me tried out a word/web game I wrote in Java. Out of a word list of the entire Oxford English dictionary, what was the first word that came up to be guessed?
Of course, the most foul word in the English language.
Somehow, I still got the job offer, but I then tracked down a profanity word list (not unlike this one) and wrote a quick script to generate a new dictionary without all of the bad words (without even having to look at the list).
For your particular case, I think comparing the search to real words sounds like the way to go with a word list like that. The alternative styles/punctuation require a bit more work, but I doubt users will use that often enough to be an issue.
a profanity filtering system will never be perfect, even if the programmer is cocksure and keeps abreast of all nude developments
that said, any list of 'naughty words' is likely to perform as well as any other list, since the underlying problem is language understanding which is pretty much intractable with current technology
so, the only practical solution is twofold:
be prepared to update your dictionary frequently
hire a human editor to correct false positives (e.g. "clbuttic" instead of "classic") and false negatives (oops! missed one!)
The only way to prevent offensive user input is to prevent all user input.
If you insist on allowing user input and need moderation, then incorporate human moderators.
Have a look at CDYNE's Profanity Filter Web Service
Testing URL
Beware of localization issues: what is a swearword in one language might be a perfectly normal word in another.
One current example of this: ebay uses a dictionary approach to filter "bad words" from feedback. If you try to enter the german translation of "this was a perfect transaction" ("das war eine perfekte Transaktion"), ebay will reject the feedback due to bad words.
Why? Because the german word for "was" is "war", and "war" is in ebay dictionary of "bad words".
So beware of localisation issues.
Regarding your "trick the system" subquestion, you can handle that by normalizing both the "bad word" list and the user-entered text before doing your search. e.g., Use a series of regexes (or tr if PHP has it) to convert [z$5] to "s", [4#] to "a", etc., then compare the normalized "bad word" list against the normalized text. Note that the normalization could potentially lead to additional false positives, although I can't think of any actual cases at the moment.
The larger challenge is to come up with something that will let people quote "The pen is mightier than the sword" while blocking "p e n i s".
I collected 2200 bad words in 12 languages: en, ar, cs, da, de, eo, es, fa, fi, fr, hi, hu, it, ja, ko, nl, no, pl, pt, ru, sv, th, tlh, tr, zh.
MySQL dump, JSON, XML or CSV options are available.
https://github.com/turalus/openDB
I'd suggest you to execute this SQL into your DB and check everytime when user inputs something.
If you can do something like Digg/Stackoverflow where the users can downvote/mark obscene content... do so.
Then all you need to do is review the "naughty" users, and block them if they break the rules.
I'm a little late to the party, but I have a solution that might work for some who read this. It's in javascript instead of php, but there's a valid reason for it.
Full disclosure, I wrote this plugin...
Anyways.
The approach I've gone with is to allow a user to "Opt-In" to their profanity filtering. Basically profanity will be allowed by default, but if my users don't want to read it, they don't have to. This also helps with the "l33t sp3#k" issue.
The concept is a simple jquery plugin that gets injected by the server if the client's account is enabling profanity filtering. From there, it's just a couple simple lines that blot out the swears.
Here's the demo page
https://chaseflorell.github.io/jQuery.ProfanityFilter/demo/
<div id="foo">
ass will fail but password will not
</div>
<script>
// code:
$('#foo').profanityFilter({
customSwears: ['ass']
});
</script>
result
*** will fail but password will not
Also late in the game, but doing some researches and stumbled across here. As others have mentioned, it's just almost close to impossible if it was automated, but if your design/requirement can involve in some cases (but not all the time) human interactions to review whether it is profane or not, you may consider ML. https://learn.microsoft.com/en-us/azure/cognitive-services/content-moderator/text-moderation-api#profanity is my current choice right now for multiple reasons:
Supports many localization
They keep updating the database, so I don't have to keep up with latest slangs or languages (maintenance issue)
When there is a high probability (I.e. 90% or more) you can just deny it pragmatically
You can observe for category which causes a flag that may or may not be profanity, and can have somebody review it to teach that it is or isn't profane.
For my need, it was/is based on public-friendly commercial service (OK, videogames) which other users may/will see the username, but the design requires that it has to go through profanity filter to reject offensive username. The sad part about this is the classic "clbuttic" issue will most likely occur since usernames are usually single word (up to N characters) of sometimes multiple words concatenated... Again, Microsoft's cognitive service will not flag "Assist" as Text.HasProfanity=true but may flag one of the categories probability to be high.
As the OP inquires, what about "a$$", here's a result when I passed it through the filter:, as you can see, it has determined it's not profane, but it has high probability that it is, so flags as recommendations of reviewing (human interactions).
When probability is high, I can either return back "I'm sorry, that name is already taken" (even if it isn't) so that it is less offensive to anti-censorship persons or something, if we don't want to integrate human review, or return "Your username have been notified to the live operation department, you may wait for your username to be reviewed and approved or chose another username". Or whatever...
By the way, the cost/price for this service is quite low for my purpose (how often does the username gets changed?), but again, for OP maybe the design demands more intensive queries and may not be ideal to pay/subscribe for ML-services, or cannot have human-review/interactions. It all depends on the design... But if design does fit the bill, perhaps this can be OP's solution.
If interested, I can list the cons in the comment in the future.
Once you have a good MYSQL table of some bad words you want to filter (I started with one of the links in this thread), you can do something like this:
$errors = array(); //Initialize error array (I use this with all my PHP form validations)
$SCREENNAME = mysql_real_escape_string($_POST['SCREENNAME']); //Escape the input data to prevent SQL injection when you query the profanity table.
$ProfanityCheckString = strtoupper($SCREENNAME); //Make the input string uppercase (so that 'BaDwOrD' is the same as 'BADWORD'). All your values in the profanity table will need to be UPPERCASE for this to work.
$ProfanityCheckString = preg_replace('/[_-]/','',$ProfanityCheckString); //I allow alphanumeric, underscores, and dashes...nothing else (I control this with PHP form validation). Pull out non-alphanumeric characters so 'B-A-D-W-O-R-D' shows up as 'BADWORD'.
$ProfanityCheckString = preg_replace('/1/','I',$ProfanityCheckString); //Replace common numeric representations of letters so '84DW0RD' shows up as 'BADWORD'.
$ProfanityCheckString = preg_replace('/3/','E',$ProfanityCheckString);
$ProfanityCheckString = preg_replace('/4/','A',$ProfanityCheckString);
$ProfanityCheckString = preg_replace('/5/','S',$ProfanityCheckString);
$ProfanityCheckString = preg_replace('/6/','G',$ProfanityCheckString);
$ProfanityCheckString = preg_replace('/7/','T',$ProfanityCheckString);
$ProfanityCheckString = preg_replace('/8/','B',$ProfanityCheckString);
$ProfanityCheckString = preg_replace('/0/','O',$ProfanityCheckString); //Replace ZERO's with O's (Capital letter o's).
$ProfanityCheckString = preg_replace('/Z/','S',$ProfanityCheckString); //Replace Z's with S's, another common substitution. Make sure you replace Z's with S's in your profanity database for this to work properly. Same with all the numbers too--having S3X7 in your database won't work, since this code would render that string as 'SEXY'. The profanity table should have the "rendered" version of the bad words.
$CheckProfanity = mysql_query("SELECT * FROM DATABASE.TABLE p WHERE p.WORD = '".$ProfanityCheckString."'");
if(mysql_num_rows($CheckProfanity) > 0) {$errors[] = 'Please select another Screen Name.';} //Check your profanity table for the scrubbed input. You could get real crazy using LIKE and wildcards, but I only want a simple profanity filter.
if (count($errors) > 0) {foreach($errors as $error) {$errorString .= "<span class='PHPError'>$error</span><br /><br />";} echo $errorString;} //Echo any PHP errors that come out of the validation, including any profanity flagging.
//You can also use these lines to troubleshoot.
//echo $ProfanityCheckString;
//echo "<br />";
//echo mysql_error();
//echo "<br />";
I'm sure there is a more efficient way to do all those replacements, but I'm not smart enough to figure it out (and this seems to work okay, albeit inefficiently).
I believe that you should err on the side of allowing users to register, and use humans to filter and add to your profanity table as required. Though it all depends on the cost of a false positive (okay word flagged as bad) versus a false negative (bad word gets through). That should ultimately govern how aggressive or conservative you are in your filtering strategy.
I would also be very careful if you want to use wildcards, since they can sometimes behave more onerously than you intend.
I agree with HanClinto's post higher up in this discussion. I generally use regular expressions to string-match input text. And this is a vain effort, as, like you originally mentioned you have to explicitly account for every trick form of writing popular on the net in your "blocked" list.
On a side note, while others are debating the ethics of censorship, I must agree that some form is necessary on the web. Some people simply enjoy posting vulgarity because it can be instantly offensive to a large body of people, and requires absolutely no thought on the author's part.
Thank you for the ideas.
HanClinto rules!
Frankly, I'd let them get the "trick the system" words out and ban them instead, which is just me. But it also makes the programming simpler.
What I'd do is implement a regex filter like so: /[\s]dooby (doo?)[\s]/i or it the word is prefixed on others, /[\s]doob(er|ed|est)[\s]/. These would prevent filtering words like assuaged, which is perfectly valid, but would also require knowledge of the other variants and updating the actual filter if you learn a new one. Obviously these are all examples, but you'd have to decide how to do it yourself.
I'm not about to type out all the words I know, not when I don't actually want to know them.
Don't. It just leads to problems. One clbuttic personal experience I have with profanity filters is the time where I was kick/banned from an IRC channel for mentioning that I was "heading over the bridge to Hancock for a couple hours" or something to that effect.
I agree with the futility of the subject, but if you have to have a filter, check out Ning's Boxwood:
Boxwood is a PHP extension for fast replacement of multiple words in a piece of text. It supports case-sensitive and case-insensitive matching. It requires that the text it operates on be encoded as UTF-8.
Also see this blog post for more details:
Fast Multiple String Replacement in PHP
With Boxwood, you can have your list of search terms be as long as you like -- the search and replace algorithm doesn't get slower with more words on the list of words to look for. It works by building a trie of all the search terms and then scans your subject text just once, walking down elements of the trie and comparing them to characters in your text. It supports US-ASCII and UTF-8, case-sensitive or insensitive matching, and has some English-centric word boundary checking logic.
I concluded, in order to create a good profanity filter we need 3 main components, or at least it is what I am going to do. These they are:
The filter: a background service that verify against a blacklist, dictionary or something like that.
Not allow anonymous account
Report abuse
A bonus, it will be to reward somehow those who contribute with accurate abuse reporters and punish the offender, e.g. suspend their accounts.
Don't.
Because:
Clbuttic
Profanity is not OMG EVIL
Profanity cannot be effectively defined
Most people quite probably don't appreciate being "protected" from profanity
Edit: While I agree with the commenter who said "censorship is wrong", that is not the nature of this answer.