Full Report
Intro Recently, I reported CVE-2017-7668 (Apache Server buffer-over-read). This is a cross-post from my personal blog where I explain how to fuzz network programs with AFL by porting techniques learned in honggfuzz into AFL. After a small chat with Dominic he asked me to re-post it here which, for me it’s an honour to do so! The reported CVE was obtained with code analysis and instrumentation of the right parts of the code (mainly core and parsing) – First, with honggfuzz I got the initial dirty test cases and then, through radamsa generated a few thousands mutations and finally AFL with the technique described here.
Analysis Summary
# Tool/Technique: American Fuzzy Lop (AFL) Fuzzing Technique for Network Programs
## Overview
This summary details the technique of adapting the American Fuzzy Lop (AFL) fuzzer, traditionally designed for file-based input, to effectively fuzz network-based programs like the Apache HTTP Server (`httpd`). This adaptation involves porting techniques learned from `honggfuzz`, specifically utilizing AFL's `afl-clang-fast` mode (persistent mode) to achieve higher execution speeds necessary for network service fuzzing. The process led to the discovery of CVE-2017-7668 in Apache Server.
## Technical Details
- Type: Tool (Fuzzer Adaptation/Technique)
- Platform: Debian GNU/Linux (used in the example), generally POSIX-compliant systems capable of compiling AFL with `afl-clang` features. Target application is Apache httpd.
- Capabilities: Enables deterministic and coverage-guided fuzzing on applications accepting input via network sockets rather than standard input, significantly boosting finding exploitable weaknesses in server software.
- First Seen: The process described is used to report CVE-2017-7668 in June 2017.
## MITRE ATT&CK Mapping
The core activity described is vulnerability discovery through automated testing, which generally maps to Defensive Evasion or Discovery preparation if used defensively, or directly to exploitation post-discovery. The vulnerability itself is related to memory corruption.
- **TA0004 - Privilege Escalation** (If the discovered flaw leads to this, e.g., exploiting the service running as root/high privilege)
- **T1068 - Exploitation for Privilege Escalation** (Indirectly, as the fuzzing finds the necessary vulnerability)
- **TA0003 - Persistence**
- **T1544.003 - Boot or Logon Autostart Execution: Windows Service** (Not directly relevant, but fuzzing targets service stability)
- **TA0002 - Execution**
- **T1059.004 - Command and Scripting Interpreter: Unix Shell** (Used to run the fuzzing setup)
*Note: As this is a vulnerability research and debugging technique, direct TTP mapping for the *fuzzing process itself* is limited. It primarily relates to **Discovery (TA0003)** focused on software weaknesses.*
## Functionality
### Core Capabilities
- **AFL Compilation:** Compiling AFL, specifically enabling the `llvm_mode` for `afl-clang-fast` (persistent mode).
- **Target Preparation:** Compiling the target application, Apache httpd, along with necessary dependencies (APR, APR Util, nghttp2).
- **Code Analysis & Instrumentation:** Analyzing the target code (specifically `core` and `parsing` modules of httpd) and instrumenting relevant sections for instrumentation feedback.
### Advanced Features
- **Network Fuzzing Adaptation:** Implementing techniques (borrowed from `honggfuzz` examples) to force AFL to fuzz network services instead of file inputs. This often involves patching the target application to run multiple iterations without restarting the service for every input.
- **Input Mutation Pipeline:** Utilizing an initial set of "dirty test cases" generated by `honggfuzz`, mutating them with `radamsa`, and feeding the corpus into AFL for guided fuzzing.
- **Persistent Mode:** Using `afl-clang-fast` to keep the target process (httpd) alive across numerous test case executions, drastically improving execution speed (though stability can degrade over long runs).
## Indicators of Compromise
This section focuses on the research tools and artifacts, not operational malware indicators.
- File Hashes: Not provided in the context.
- File Names: `afl-fuzz`, `afl-clang-fast`, `radamsa`, `honggfuzz`, `httpd`.
- Registry Keys: N/A (Linux environment).
- Network Indicators: N/A (Fuzzing target is local setup; no C2 mentioned).
- Behavioral Indicators: Rapid creation and execution of numerous network requests/inputs against configured local web server instance, potentially leading to crashes or assertion failures in the target process.
## Associated Threat Actors
- **Javier Jimenez (Researcher):** Responsible for adapting the technique and reporting CVE-2017-7668.
- **Dominic (Mentioned):** Involved in encouraging the cross-posting of the research.
- **Robert Swiecky (Inspiration):** Mentioned for previous work fuzzing Apache with `honggfuzz`, whose persistence technique was ported to AFL.
- **Apache Security Team:** The team receiving the coordinated vulnerability disclosure.
## Detection Methods
Detection methods described are specific to identifying the AFL environment setup during analysis:
- **Signature-based detection:** Looking for binaries compiled with AFL instrumentation flags (e.g., checks for specific environment variables or unique function hooks introduced by LLVM instrumentation).
- **Behavioral detection:** Monitoring for an unusually high volume of synthesized or mutated network requests directed at a web server instance in a short period, especially if the source appears to be a testing framework runner.
- **YARA rules:** Not explicitly provided.
## Mitigation Strategies
The vulnerability identified (CVE-2017-7668) is a buffer-over-read related to core and parsing components of Apache httpd.
- **Prevention Measures:**
- Applying patches for CVE-2017-7668 (and all other relevant security updates) to the Apache httpd server.
- Using robust input validation, especially in packet parsing logic.
- **Hardening Recommendations:**
- Not running web servers (like httpd) as the root user (though the final examples required root access for `unshare` functionality setup demonstration).
- Ensuring development and testing environments utilize automated testing tools like fuzzers to find memory safety issues prior to deployment.
## Related Tools/Techniques
- **American Fuzzy Lop (AFL):** The core fuzzing engine.
- **honggfuzz:** Fuzzer whose techniques (specifically persistence/multi-iteration testing) were ported to AFL.
- **radamsa:** Used for initial input mutation to grow the seed corpus.
- **CVE-2017-7668:** The specific vulnerability identified through this fuzzing process in Apache Server.
- **AFL Persistent Mode (`afl-clang-fast`):** The key technique enabling high throughput for network service fuzzing.