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Audit Logging

Audit logs provide a hash-annotated record of interactions between Burp context and AI backend outputs. They support review and accidental-corruption checks, but the current unkeyed hashes do not authenticate a record against an editor who can rewrite both payload and hash. Universal trace correlation lives in the separate AI Request Logger; the audit event stream does not attach a trace ID to every event.

Event Chain

What Is Logged

Each event entry can include:

  • timestamp,

  • event type (prompt, agent_chunk, prompt_complete, scanner/MCP events),

  • a trace ID on selected scanner/MCP event families (not on every supervisor prompt/chunk/completion event),

  • redacted prompt bundle and hashes,

  • backend metadata,

  • response callback chunks (currently one complete chunk for built-in backends),

  • launch metadata (see below).

For chat dispatches, the prompt bundle records the current text argument sent through AgentSupervisor.sendChat. It is not a full wire transcript: conversation history is supplied separately, and HTTP-capable backends can receive the active agent profile through a separate systemPrompt argument that is not serialized into the bundle. CLI backends instead prepend that profile to their user text. Treat the bundle as a review artifact for the captured dispatch, not as proof of every byte a provider received.

Launch Metadata

Every context-driven chat launch (right-click → any AI action) stamps the resulting prompt event and the PromptBundle saved under bundles/ with:

Field
Values
Meaning

promptSource

FIXED | CUSTOM_SAVED | CUSTOM_AD_HOC

Origin of the prompt. Canned actions report FIXED; saved library entries report CUSTOM_SAVED; free-form one-offs report CUSTOM_AD_HOC.

contextKind

HTTP_SELECTION | SCANNER_ISSUE

Which menu the launch came from.

promptId

UUID

Identifier of the saved custom prompt (only for CUSTOM_SAVED).

promptTitle

string

Human-readable title of the saved custom prompt (only for CUSTOM_SAVED).

These also land in the metadata map of matching AiRequestLogger entries (PROMPT_SENT, RESPONSE_COMPLETE, ERROR).

Example filter for recent custom-prompt runs:

Trace ID Correlation

The AI Request Logger generates and carries the following correlation IDs. Do not assume the same ID is present in every audit.jsonl event: current supervisor prompt, agent_chunk, and prompt_complete records omit it, while selected scanner/MCP audit payloads may include one.

Trace ID pattern
Emitted by
Links

chat-turn-{UUID}

ChatPanel

The prompt, any MCP tool chain steps, and the final response.

agent-turn-{UUID}

AgentSupervisor

Prompt dispatch and result outside the chat flow.

scanner-job-{UUID}

Active and passive scanner (single-request)

Scanner analysis dispatch and outcome.

scanner-batch-{UUID}

Passive scanner batch analysis (BatchAnalysisQueue)

A single AI call covering 3–5 grouped requests, with per-request dispatch events sharing the ID.

adaptive-payload-{VULN_CLASS}

AdaptivePayloadEngine

AI-driven context-aware payload generation, cached by {vulnClass}:{techStack} for 30 minutes.

Use the AI Request Logger UI or its optional rolling JSONL files for end-to-end trace filtering. Join audit prompt bundles by their session/backend/timestamp and launch metadata where necessary.

Log Format

Logs use JSON Lines (.jsonl); each line is a standalone JSON object.

Security & Integrity

  • Each event carries a per-event SHA-256 checksum of the serialized payload in the payloadSha256 field. The checksum is independent per record — there is no keyed MAC, signature, external anchor, or Merkle chain linking entries.

  • MCP tool calls include argument and result checksums (argsSha256, resultSha256) for correlation and comparison across records.

  • With determinism enabled, identical inputs are easier to compare across runs (see Determinism & Salt).

  • The file is ordinary append-oriented plaintext. A process with write access can alter a payload and recompute its checksum, or delete/reorder lines. Use filesystem ACLs, append-only storage, remote log shipping, signatures, or another external integrity control when authenticity matters.

How to Enable

  1. Open Privacy & Logging tab in Settings.

  2. Toggle Audit Logging ON.

File Locations

Path
Contents

~/.burp-ai-agent/audit.jsonl

Main append-oriented event log.

~/.burp-ai-agent/bundles/

Prompt bundle snapshots.

~/.burp-ai-agent/contexts/

Reserved context directory. The current runtime creates it, but no production caller writes standalone context snapshots. Context may still be embedded in prompt bundles.

~/.burp-ai-agent/logs/

Rolling AI Request Logger JSONL files (opt-in).

Use Cases

  • Supporting compliance evidence when paired with external retention/integrity controls.

  • Reproducibility and review of AI-assisted findings.

  • Team quality control and diagnostics.

  • Review of captured prompt metadata and response chunks; use the AI Request Logger for complete trace-ID filtering.

Related Pages

PreviousLimitations & Hallucinations
NextAI Request Logger

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