API Upload Test

Intrusion detection
for web applications

Intrusion detection
for web applications

Łukasz Pilorz

Application Security Team, Allegro.pl

Reasons for using
IDS solutions
● known weaknesses and vulnerabilities
● balance between security and usability
rd
●
3 -party applications and libraries
● insecure client software
● additional layer of security
● fear, uncertainty, doubt

IDS, IPS or WAF?

IDS purpose

● data source for post-intrusion analysis
● real-time intrusion investigation
● holy grail: intrusion prevention

How can we detect unknown attacks?

Positive security model

● “accept known good” mantra
● allowed byte ranges
● regular expressions
● allowed variables whitelist

What about encoded (base64, weak encryption,
multiple charsets) or complex (HTML, file
upload) data?

Positive security model

● when application changes, whitelist has to
change too
● lots of alerts

● http://p1.tld/p2/p3.php/p4/p5=p6,p7?p8&p9=p0

● real-time protection? block them all!
● sanitizing wrong input could help

Why can't we do this in the application itself?

It's easier to fix applications,
than detect attacks

● usually true
●
3rd party software and libraries
● unknown attack methods

● security filters adding new vulnerabilities
● example: HTML filters

HTML filters review – March
2008
Tested: 5 popular anti-XSS HTML filters (PHP)

Results:
● 3/5 vulnerable to XSS (+1 already known 0-day)
● 2/5 included PHP code execution bugs (kses,
htmLawed)
● alternative syntax like Textile or Markdown also
not safe from XSS

Negative security model

● blacklist detection rules
● far less alerts
● classification by attack type, priority, etc.
● generic rules: often too general, false positives
● specific rules: very limited, often outdated

How to detect unknown attacks?

Examples

● Snort – known exploits

● ModSecurity Core Rules – generic

● PHPIDS – generic, focused on XSS

PHPIDS

● LGPL licensed IDS library for PHP applications
● impact rating for each malicious request
● could be added in auto_prepend_file, without
modifying application code
● attempts to detect unknown attack patterns

http://php-ids.org/

What are we trying to detect?

● automated exploits
● automated vulnerability scanners
● manual attacks
● uncommon user behaviour

● intrusion vs vulnerability testing

How to recognize source type?

A1 - Cross Site Scripting (XSS)

● most common: <script, document.cookie
● dangerous HTML tags and attributes
● breaking out of HTML attribute
● JavaScript keywords

● comparing request and response

● PHPIDS regular expressions

XSS from attacker's view

● needs just one byte to detect vulnerability,
e.g. “, <, (
● easy to make it look innocent

<a href=”http://tested.site.tld/page.php?
id=article">Interesting article</a>
<script>[Google Analytics]...

● usually needs at least several requests to
prepare working attack (for custom application)

XSS – detection

● hard to detect less common vulnerability testing
patterns
● recognizing malicious XSS code is easier
● time window between finding vulnerability and
developing exploit
● real-time detection could prevent attack
rd
How to detect DOM-based XSS or 3 party
JavaScript/CSS modifications?

XSS – reducing false positives

● different rules for public and private application
sections
● check for persistent XSS after HTML filtering
(response buffering or PHPIDS)
● don't alert when only single keyword/char
matches rule (skip non-malicious XSS)

● raise impact rating for suspicious or missing
Referer headers
● don't even think about “trusted IPs”

A2 – Injection Flaws

● paranoid mode: blocking semicolon and quotes
● checking for SQL (or other language) keywords

● 2.0, 2-0, 2-1, 2;[query]
● val'||', val';[query]
● 2 AND 1=1, 2 AND 1=2
● 2 UNION...SELECT [query]
● /*...*/, /*!...*/

● “page.tld/page?var=1/*&UNION SELECT*/”

SQL Injection

● relatively easy to detect malicious attacks
● many false positives, if we want to detect
vulnerability testing
● good results with whitelisting

● reducing false positives by checking traffic
between application and database (or in the
application, before executing query)
● real-time reporting of SQL query errors

Command/Code Injection

● much wider range of malicious code than for
SQL Injection
● detect vulnerability testing, not exploits
● reducing false positives by eliminating known
vectors

● common commands and functions
● `, {${, <?, <%
● real-time reporting of application errors

Other injection flaws

● LDAP

● XPath

● XSLT

● HTML

● HTTP

A3 – Malicious File Execution

● affects mostly PHP

● external URL in request (http://, ftp://)
● wrappers (data:, php:, ogg:, zlib:, zip:)
● /var/log/httpd/
● /proc/self/environ + User-Agent
● /, ../

● upload containing PHP code
● upload filename & extension

A4 – Insecure
Direct Object Reference
● easier to fix than detect
● whitelisting often doesn't help

● we can try to detect data harvesting tools
● multiple requests to the same page, with
different set of parameters
● repeating requests to a single page or a small
subset of pages
● small mistakes in automatically generated
requests (Referer, null bytes, missing headers
or cookies)

A5 – Cross Site Request Forgery
(CSRF)
● why black hats love CSRF?
● again, it's really easier to fix than detect

● external or missing Referer header
● missing cookies
● Accept header
● user trying to perform action while logged out
● user trying to remind password while logged in
● broken application flow

● Referer-less redirects, clickjacking

A6 – Information Leakage and
Improper Error Handling
● monitoring outbound traffic (e.g. ModSecurity)
● application code, HTML comments, error
messages (esp. SQL)
rd
●
3 party software may leak undocumented or
non-standard error messages
● what information should be treated as leakage
(and how IDS knows it)?
● Blind SQL Injection

Forcing errors

● var[]=1
● 1.1, 1x, ./1, /1
● “, ', !, %0A, %00

● wrong type of data
● wrong format of session identifier
● DoS
● ...

● too many possibilities to check requests

A7 – Broken Authentication and
Session Management

Session hijacking detection
● another one that is easier to fix in the
application itself (or rather “fix”)

After identifier is stolen:
● IP address change during session
● headers changed/missing during session

Before:
● tampering session identifiers
● XSS

Session hijacking
– attacker's view

● sniffing traffic
Spoof IP, everything else you already have.

● XSS
You don't need to hijack session identifier,
just force the victim to do whatever you
wanted.

● Referer header

A8/A9 – Insecure Cryptographic
Storage and Communications
● not much to do for an IDS
(at least on the server side)

● passing base64-encoded or weakly encrypted
values to the client
● WAF protection against tampering
● may be decrypted on client side and leak
information

● general brute-force attacks detection

A10 – Failure to Restrict URL
Access
● IDS has no information about user rights in the
application

● known vulnerabilities in libraries/include files
● brute-force detection may deal with fuzzing
● broken application flow

● whitelisting

● IPS/WAF as a hotfix solution

Log, block, alert

3-tier solution

Tier 1:
● log everything you can

Tier 2:
● detailed log of detected attack attempts

Tier 3:
● possible intrusions and bypasses

Tier 1

● log everything you can

● all application errors
(with their context)

● full requests
(URL, headers, cookies, body)

● full responses
(HTTP code, headers, body)

Tier 2

● detailed log of detected attack attempts

● IDS alerts
● combined data from several sources

● including vulnerability testing patterns
● including blocked/sanitized requests
● optionally: requests following blocked one

Tier 3
● possible intrusions and bypasses

● alerts that require manual verification

● generate as much as you are able to check
manually

● skip blocked requests

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