Research

How Strike7 Uses Agent Skills for Autonomous Attack Execution

Strike7 uses modular Agent Skills — self-describing capability definitions that AI agents dynamically select based on environmental context — to enable far more adaptive autonomous penetration testing than fixed-workflow tools.

What Agent Skills Are and Why They Matter in Pentesting

Agent Skills are structured modules that describe an action the agent can perform, the conditions under which it should be used, and the tools it is allowed to invoke. This enables an AI system to reason about capabilities at a higher level and to select the right technique for the environment it is facing.

In Strike7, Agent Skills represent focused offensive capabilities such as WAF bypass techniques, exploitation logic tied to specific CVEs, technology-specific attack patterns, and protocol-aware attack flows.

SKILL.md as a Practical Format for Security Skills

Strike7 uses a markdown-based definition format for skills. Each skill declares a clear name and purpose, includes security-relevant metadata, and specifies explicit tool permissions so execution remains controlled.

This design makes skills easier to review and govern. It also helps skills stay portable across environments because the agent can reason over the metadata without coupling to internal implementation details.

What the Skill Definition Enables

• Security teams can review what a skill is intended to do and why it would be selected.
• Tool usage can be constrained through explicit permissions to support least-privilege execution.
• Skills can be shared, cached, or distributed without tightly coupling them to the agent core.
• The agent can select skills based on metadata rather than relying on hardcoded attack chains.

Skill Registry Architecture

At the center of the system is the Skill Registry. Its job is to discover skills, index them by meaningful security context, and return the most relevant skills when the agent asks what it should use next.

The registry builds multiple matching indexes to keep selection fast and deterministic. Rather than searching through everything each time, the registry uses context signals to match a smaller, relevant set of skills.

What the Registry Indexes

• WAF vendors mapped to vendor-specific bypass skills when a WAF is detected.
• CVE identifiers mapped to exploitation skills when matching CVEs are identified.
• Detected technologies mapped to technology-specific attack skills.
• Detected protocols mapped to protocol-aware skills where protocol context matters.

The registry's responsibility is deliberately narrow and practical: it answers the question of which skills match the current attack context. It does not need to know how each skill is implemented.

Context-Aware Skill Matching

During an engagement, Strike7 continuously builds and refreshes an execution context — whether a WAF is present and which vendor is in use, which CVEs appear relevant, what technologies are detected, and which protocols are observed.

When the agent enters an execution phase, it asks the Skill Registry for skills that match this context. The registry returns skills along with a clear match reason, such as a WAF vendor match, a CVE match, or a technology match. This shifts the workflow from generic probing toward targeted execution based on real conditions.

Integration with the Triage Agent

Skill selection is integrated into triage. The Triage Agent focuses on understanding the environment and identifying what matters next. Once it has enough context, it requests relevant skills from the registry and triggers loading of the matched capabilities.

This design ensures that bypass or exploit logic is not loaded by default. Instead, it becomes available when there is a strong contextual reason to use it — keeping execution focused and reducing unnecessary noise.

A Hybrid Strategy for Skills

Strike7 uses a hybrid approach that balances baseline reliability with on-demand extensibility.

In-Built Skills

In-built skills provide baseline capabilities that are always available, covering the foundation of a security assessment and supporting consistent results across environments.

• Reconnaissance and initial mapping of exposed surfaces.
• Enumeration of services, identities, and reachable components.
• Core testing primitives that do not require external marketplace retrieval.

Dynamic Skills

Dynamic skills are loaded when the environment indicates they are relevant — sourced from a marketplace, cached from prior engagements, or developed as customer-specific extensions.

• Loaded when a specific WAF vendor is identified and a matching bypass exists.
• Loaded when a specific CVE is detected and a verified exploit skill is available.
• Loaded when a specific technology is identified and targeted attack logic is appropriate.

Why This Design Changes AI Pentesting Outcomes

• Execution becomes context-driven rather than limited to a fixed, linear workflow.
• Noise is reduced because irrelevant techniques are less likely to be loaded or executed.
• Success rates improve because skills can be targeted to specific defenses and technologies.
• Reasoning stays separate from execution, supporting clearer governance and safer operation.
• Tool permissions can be explicitly controlled, supporting least-privilege execution and auditing.

Closing Thoughts

Agent Skills provide a scalable way to package capabilities so an AI system can select and execute them responsibly. Strike7's focus is not on inventing Agent Skills, but on operationalizing them for real-world penetration testing through context-aware matching, controlled execution, and hybrid skill sourcing.

As environments become more complex and defenses more adaptive, pentesting systems need the ability to observe, adapt, select the right technique, and execute with intent. Agent Skills provide a practical foundation for that model.