Description
llama-cpp-python is the Python bindings for llama.cpp. `llama-cpp-python` depends on class `Llama` in `llama.py` to load `.gguf` llama.cpp or Latency Machine Learning Models. The `__init__` constructor built in the `Llama` takes several parameters to configure the loading and running of the model. Other than `NUMA, LoRa settings`, `loading tokenizers,` and `hardware settings`, `__init__` also loads the `chat template` from targeted `.gguf` 's Metadata and furtherly parses it to `llama_chat_format.Jinja2ChatFormatter.to_chat_handler()` to construct the `self.chat_handler` for this model. Nevertheless, `Jinja2ChatFormatter` parse the `chat template` within the Metadate with sandbox-less `jinja2.Environment`, which is furthermore rendered in `__call__` to construct the `prompt` of interaction. This allows `jinja2` Server Side Template Injection which leads to remote code execution by a carefully constructed payload.
EPSS Score:
1%
Comprehensive Technical Analysis of EUVD-2024-1433
1. Vulnerability Assessment and Severity Evaluation
Vulnerability Description:
The vulnerability in llama-cpp-python arises from the use of a sandbox-less jinja2.Environment to parse and render chat templates from .gguf files. This allows for Server Side Template Injection (SSTI), which can lead to remote code execution (RCE) if a maliciously crafted payload is used.
Severity Evaluation:
- Base Score: 9.7 (CVSS:3.1)
- Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:H
The high base score indicates a critical vulnerability due to the potential for remote code execution, which can compromise confidentiality, integrity, and availability. The attack vector is network-based (AV:N), requires low complexity (AC:L), no privileges (PR:N), and user interaction (UI:R). The impact is complete (S:C) with high confidentiality, integrity, and availability impacts (C:H/I:H/A:H).
2. Potential Attack Vectors and Exploitation Methods
Attack Vectors:
- Network-Based Attack: An attacker can exploit this vulnerability over the network by sending a specially crafted
.gguffile containing malicious Jinja2 templates. - User Interaction: The attack requires some form of user interaction, such as loading a malicious
.gguffile.
Exploitation Methods:
- SSTI Exploitation: The attacker can inject malicious code into the Jinja2 templates, which will be executed by the
jinja2.Environmentduring the parsing and rendering process. - Payload Crafting: The payload can include commands to execute arbitrary code on the server, leading to RCE.
3. Affected Systems and Software Versions
Affected Software:
llama-cpp-pythonversions 0.2.30 through 0.2.71.
Vendor and Product Information:
- Vendor: abetlen
- Product: llama-cpp-python
4. Recommended Mitigation Strategies
Immediate Mitigation:
- Patching: Upgrade to a version of
llama-cpp-pythonthat includes the fix for this vulnerability. - Input Validation: Implement strict input validation and sanitization for
.gguffiles to prevent malicious templates from being processed. - Sandboxing: Use a sandboxed environment for parsing and rendering Jinja2 templates to limit the impact of any malicious code.
Long-Term Mitigation:
- Code Review: Conduct a thorough code review to identify and mitigate similar vulnerabilities in other parts of the codebase.
- Security Training: Provide security training for developers to ensure they are aware of common vulnerabilities and best practices for secure coding.
5. Impact on European Cybersecurity Landscape
Regulatory Compliance:
- GDPR: The vulnerability could lead to data breaches, impacting GDPR compliance and resulting in potential fines and legal actions.
- NIS Directive: Organizations in critical sectors must ensure they are compliant with the NIS Directive, which mandates robust cybersecurity measures.
Economic Impact:
- Financial Losses: Organizations may face financial losses due to data breaches, downtime, and remediation costs.
- Reputation Damage: Compromised systems can lead to loss of customer trust and damage to the organization's reputation.
National Security:
- Critical Infrastructure: If exploited in critical infrastructure, this vulnerability could have severe implications for national security.
6. Technical Details for Security Professionals
Vulnerability Details:
- Root Cause: The use of a sandbox-less
jinja2.Environmentto parse and render chat templates from.gguffiles. - Exploitation: The
Jinja2ChatFormatterparses the chat template within the metadata without proper sandboxing, allowing for SSTI.
Detection and Monitoring:
- Logging: Implement comprehensive logging to monitor for suspicious activities related to
.gguffile processing. - Intrusion Detection: Use intrusion detection systems (IDS) to detect and alert on potential SSTI attacks.
Incident Response:
- Containment: Isolate affected systems to prevent further spread of the attack.
- Eradication: Remove malicious templates and ensure all systems are patched.
- Recovery: Restore systems to a known good state and verify the integrity of all data.
References:
By addressing this vulnerability promptly and thoroughly, organizations can mitigate the risk of remote code execution and protect their systems and data from potential attacks.