attack-surface.md

Attack Surface Analysis for lllyasviel/fooocus

Attack Surface: Prompt Injection

Description: Exploiting vulnerabilities in how Fooocus processes user-provided text prompts to manipulate image generation in unintended ways, bypass intended filters, or potentially execute unintended actions within the application's context. Fooocus Contribution: Fooocus's core functionality relies on complex prompt processing to guide image generation. The sophistication of prompt features (styles, negative prompts, etc.) increases the complexity of parsing and interpretation, creating potential injection points if not handled with extreme care. Fooocus's specific prompt processing logic is the direct source of this attack surface. Example: A malicious user crafts a prompt designed to bypass content filters implemented in Fooocus, generating images that violate intended usage policies. Or, a prompt could be crafted to subtly manipulate the style or content generation in a way that is harmful or misleading, even if not explicitly blocked by filters. Impact: Bypass of intended content restrictions, generation of undesirable or harmful content, potential for resource abuse, reputational damage, and in extreme cases, if prompt processing interacts with other system components insecurely, limited application-level compromise. Risk Severity: High Mitigation Strategies:

• Developers: Implement rigorous input sanitization and validation specifically tailored to the nuances of prompt processing in Stable Diffusion models. Employ robust prompt parsing techniques that isolate user input from execution logic. Consider using prompt rewriting or filtering mechanisms designed to neutralize potentially harmful prompt structures. Sandbox prompt processing to limit the impact of malicious prompts. Regularly test prompt processing logic against a wide range of potentially malicious inputs.

Attack Surface: Malicious Model Loading

Description: The risk introduced by allowing users to load and execute custom or untrusted machine learning models within Fooocus, potentially leading to arbitrary code execution or other malicious activities. Fooocus Contribution: If Fooocus provides functionality for users to load custom models, or if the default model download process lacks sufficient security measures (integrity checks, secure channels), Fooocus directly enables this attack surface. The model loading and execution mechanisms within Fooocus are the direct pathway for this risk. Example: A user loads a seemingly innocuous custom Stable Diffusion model from an untrusted online source. Unbeknownst to the user, this model contains embedded malicious code that executes when the model is loaded by Fooocus, granting the attacker control over the Fooocus application or the system it is running on. Impact: Remote code execution on the system running Fooocus, data exfiltration, denial of service, complete system compromise, potential for supply chain attacks if malicious models are widely distributed. Risk Severity: Critical Mitigation Strategies:

• Developers: Strongly discourage or disable custom model loading functionality if security cannot be guaranteed. If custom model loading is essential, implement mandatory security measures: require model signing and verification from trusted sources, implement model scanning and analysis tools to detect potentially malicious code before loading, and enforce strict sandboxing for model execution to limit the impact of compromised models. Provide clear and prominent warnings to users about the extreme risks of loading untrusted models. For default model downloads, use HTTPS and implement robust integrity checks (e.g., checksum verification) to prevent model tampering during download.

Attack Surface: Fooocus's Dependency Management leading to Vulnerabilities

Description: While dependency vulnerabilities are not inherently Fooocus's code, Fooocus's management and selection of dependencies, and its responsibility to maintain them, directly contributes to this attack surface. Outdated or vulnerable dependencies used by Fooocus can be exploited. Fooocus Contribution: Fooocus relies on a complex ecosystem of Python libraries. The choice of these libraries and the responsibility for keeping them updated and secure rests with the Fooocus development team. Failure to properly manage dependencies directly exposes Fooocus users to vulnerabilities within those libraries. Example: Fooocus uses an outdated version of a core library (e.g., a specific version of torch or diffusers) that has a publicly known remote code execution vulnerability. An attacker could exploit this vulnerability by crafting a specific input or interaction with Fooocus that triggers the vulnerable code path within the outdated dependency. Impact: Remote code execution, denial of service, information disclosure, depending on the specific vulnerability in the dependency. The impact can be as severe as system compromise if a critical dependency is exploited. Risk Severity: High to Critical (depending on the severity of the dependency vulnerability). Mitigation Strategies:

• Developers: Implement a robust dependency management strategy. Maintain a clear inventory of all direct and transitive dependencies. Regularly update all dependencies to the latest secure versions. Automate dependency scanning using tools like pip-audit or safety to proactively identify and address known vulnerabilities. Implement a process for quickly patching or mitigating newly discovered dependency vulnerabilities. Pin dependency versions in build processes to ensure consistent and tested environments, while still regularly reviewing and updating these pinned versions.