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The Static-Analysis Confidence Gap in AI-Agent Software

Static analysis can find real defects in an agent's software substrate, but a clean report cannot prove that model-mediated intent, framework semantics, delegated authority, and multi-step behavior are secure. This series measures that boundary and develops an honest assurance envelope for reporting what was checked, what was missed, and what remains unknown.

Murali Chillakuru·10 articles
  1. 1
    What a Clean Static-Analysis Report Actually Proves

    A report with no findings is evidence about a bounded search, not a certificate of safety — and for AI-agent software that boundary is unusually narrow.

  2. 2
    Measuring Static Analysis on AI-Agent Vulnerabilities

    You cannot borrow a conventional benchmark's recall for agent code — so measuring what a scanner catches on agent-specific flows is a study you have to design from scratch.

  3. 3
    The Agent-Framework Modeling Gap

    The most fixable reason a scanner misses an agent bug is not the model — it is the mundane framework glue between source and sink that the analyzer was never taught to trace.

  4. 4
    Model-Mediated Taint Tracking

    A language model is a transform in the middle of a data-flow path — one that can preserve taint, amplify it from data into instruction, and never be trusted to remove it.

  5. 5
    Modeling Agent-Specific Sources, Sinks, and Trust Boundaries

    Static analysis ships a library of sources and sinks for conventional software; an agent needs a new, reusable catalog because its untrusted inputs and dangerous outputs are ones that library never named.

  6. 6
    False Positives and Function-Breaking Remediation

    A static-analysis finding is a hypothesis, not a verdict — and the fix that satisfies the query can be the fix that breaks the agent.

  7. 7
    Agentic Risks Beyond Source-to-Sink Analysis

    Taint analysis owns one slice of agent risk; the rest is decided by the model, the deployment, or the running state — where a static tool cannot look.

  8. 8
    When Safe Operations Compose into an Unsafe Plan

    Every step an agent takes can pass its own local check while the sequence they form is an exfiltration — because safety is not compositional.

  9. 9
    Static Analysis as a Gate for AI-Generated Code

    When a model writes the code at volume, the scanner stops being advisory and becomes load-bearing — which is exactly when its blind spots and its gameability start to matter.

  10. 10
    An Honest Assurance Report for Agent Software

    Replace the pass/fail verdict with a coverage manifest — a structured statement of exactly what was modeled, what was excluded, and what residual risk still needs a runtime test.