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Attack Tree Analysis for cloudflare/pingora

Objective: To compromise an application using Pingora by exploiting weaknesses or vulnerabilities within the project itself, specifically focusing on high-risk areas. The primary goals are Denial of Service and, if possible, achieving Remote Code Execution.

Attack Tree Visualization

[Attacker's Goal: Compromise Application via Pingora]
├── [1. Denial of Service (DoS)]
│   ├── [1.1 Exploit Logic Errors in Request Handling]
│   │   ├── [1.1.1 Malformed HTTP Requests]
│   │   │   ├── [1.1.1.1  HTTP/2 Header Frame Flooding (specific to HTTP/2 handling)] ==>
│   │   │   └── [1.1.1.5  Slowloris-style attacks] ==>
│   │   └── [1.1.3  Exploit Callback Logic]
│   │       └── [1.1.3.1  Long-running or blocking callbacks] ==>
│   ├── [+1.2 Resource Exhaustion (Pingora-Specific)+] ==>
│   │   ├── [1.2.1 Connection Pool Exhaustion]
│   │   │   └── [1.2.1.1  Flood with new connections, exceeding configured limits] ==>
│   │   └── [1.2.3 CPU Exhaustion]
│   │       ├── [1.2.3.1  Complex regular expressions in routing or filtering (ReDoS)] ==>
│   │       └── [1.2.3.2  CPU-intensive operations in custom filters or callbacks] ==>
├── [2. Information Disclosure]
│   ├── [2.1  Cache Poisoning/Manipulation]
│   │   ├── [+2.1.1  Inject malicious responses into the cache+] -->
└── [+6. Gain Control of Pingora Process (RCE)+]
    ├── [6.1  Exploit Memory Corruption Vulnerabilities]
    │   ├── [6.1.1  Buffer overflows in request parsing or handling] -->
    │   ├── [6.1.2  Use-after-free vulnerabilities in asynchronous operations] -->
    │   └── [6.1.3  Integer overflows leading to memory corruption] -->
    ├── [6.2  Exploit Deserialization Vulnerabilities]
    │   └── [6.2.1  If Pingora deserializes untrusted data, exploit vulnerabilities in the deserialization process] -->
    └── [6.3  Exploit Vulnerabilities in External Libraries]
        └── [6.3.1  Vulnerabilities in libraries used by Pingora] -->

Attack Tree Path: 1. Denial of Service (DoS)

  • 1.1.1.1 HTTP/2 Header Frame Flooding:

    • Description: The attacker sends a rapid stream of HTTP/2 header frames to the Pingora server, overwhelming its ability to process them. This can consume resources and prevent legitimate requests from being handled.
    • Likelihood: Medium
    • Impact: High
    • Effort: Low
    • Skill Level: Intermediate
    • Detection Difficulty: Medium
    • Mitigation: Implement strict rate limiting on HTTP/2 header frames. Monitor for unusual HTTP/2 traffic patterns.

  • 1.1.1.5 Slowloris-style attacks:

    • Description: The attacker establishes multiple connections to the Pingora server but sends data very slowly, keeping the connections open for an extended period. This can exhaust connection resources and prevent legitimate clients from connecting.
    • Likelihood: Medium
    • Impact: High
    • Effort: Low
    • Skill Level: Intermediate
    • Detection Difficulty: Medium
    • Mitigation: Configure appropriate connection timeouts. Implement connection limiting and monitoring.

  • 1.1.3.1 Long-running or blocking callbacks:

    • Description: If custom callbacks within Pingora are poorly written and take a long time to execute or block the main event loop, they can significantly degrade performance and potentially lead to a denial of service.
    • Likelihood: Medium
    • Impact: Medium to High
    • Effort: Low (if the attacker can influence callback code)
    • Skill Level: Intermediate
    • Detection Difficulty: Medium
    • Mitigation: Ensure all custom callbacks are short-lived and non-blocking. Thoroughly review and test callback code. Implement timeouts for callbacks.

  • [+] 1.2 Resource Exhaustion (Pingora-Specific):

    • Description: This is a broad category encompassing attacks that aim to consume excessive resources (CPU, memory, connections) on the Pingora server itself, leading to performance degradation or a complete crash.
    • Likelihood: Medium to High (depending on the specific sub-attack)
    • Impact: High
    • Effort: Low to Medium (depending on the specific sub-attack)
    • Skill Level: Intermediate
    • Detection Difficulty: Medium
    • Mitigation: Implement comprehensive resource limits and monitoring. This includes connection limits, memory limits, CPU usage limits, and request/response size limits.

  • 1.2.1.1 Flood with new connections:

    • Description: The attacker rapidly opens a large number of connections to the Pingora server, exceeding the configured connection limits and preventing legitimate clients from connecting.
    • Likelihood: Medium
    • Impact: High
    • Effort: Low
    • Skill Level: Intermediate
    • Detection Difficulty: Medium
    • Mitigation: Configure reasonable connection limits. Implement rate limiting and connection monitoring.

  • 1.2.3.1 Complex regular expressions (ReDoS):

    • Description: The attacker crafts a malicious regular expression that causes the regex engine to consume excessive CPU time when processing certain inputs. This can lead to CPU exhaustion and denial of service.
    • Likelihood: Medium
    • Impact: High
    • Effort: Medium
    • Skill Level: Intermediate
    • Detection Difficulty: Medium
    • Mitigation: Avoid using complex or user-controllable regular expressions. Use a regex engine with ReDoS protection or carefully analyze and test all regexes. Implement CPU usage limits.

  • 1.2.3.2 CPU-intensive operations in custom filters/callbacks:

    • Description: Similar to blocking callbacks, custom filters or callbacks that perform CPU-intensive operations can degrade performance and potentially lead to DoS.
    • Likelihood: Medium
    • Impact: Medium to High
    • Effort: Low (if the attacker can influence custom code)
    • Skill Level: Intermediate
    • Detection Difficulty: Medium
    • Mitigation: Ensure custom code is well-optimized and avoids unnecessary CPU-intensive operations. Implement CPU usage limits and monitoring.

Attack Tree Path: 2. Information Disclosure

  • [+] 2.1.1 Inject malicious responses into the cache: * Description: If caching is enabled and misconfigured, an attacker might be able to inject crafted responses into the cache. Subsequent legitimate requests would then be served the attacker's malicious content. * Likelihood: Low * Impact: High * Effort: Medium * Skill Level: Intermediate * Detection Difficulty: Hard * Mitigation: Implement strict cache key validation. Ensure that cached responses are properly validated before being served. Consider using cryptographic signatures for cached content.

Attack Tree Path: [+] 6. Gain Control of Pingora Process (RCE)

  • Description: This represents the most severe outcome, where an attacker gains the ability to execute arbitrary code on the Pingora server. This would grant them complete control over the server and potentially the entire application.

  • Likelihood: Very Low (due to Rust's memory safety)

  • Impact: Very High

  • Effort: Very High

  • Skill Level: Expert

  • Detection Difficulty: Very Hard

  • Mitigation: Focus on preventing any potential memory corruption vulnerabilities. Minimize the use of unsafe code in Rust. Keep all dependencies up-to-date. Conduct regular security audits and penetration testing. Implement strong system-level security controls (e.g., SELinux, AppArmor).

    • 6.1.1 Buffer overflows: (Very Low Likelihood) - Exploiting buffer overflows in request parsing.
    • 6.1.2 Use-after-free: (Very Low Likelihood) - Exploiting use-after-free vulnerabilities in asynchronous code.
    • 6.1.3 Integer overflows: (Low Likelihood) - Integer overflows that could lead to memory corruption.
    • 6.2.1 Deserialization Vulnerabilities: (Low Likelihood) - Exploiting vulnerabilities if Pingora deserializes untrusted data.
    • 6.3.1 Vulnerabilities in External Libraries: (Low Likelihood) - Exploiting vulnerabilities in libraries used by Pingora.