cendor-acttrace 1.0.0

Audit: a tamper-evident, hash-chained, auto-populated record of every AI decision — verifiable offline. Evidence, not a compliance guarantee.

cendor-acttrace

A tamper-evident, append-only record of every AI decision — what model, what context, what it cost, which tools, and who signed off — mapped to control templates and exportable as an evidence pack. No database, no infra: integrity comes from a hash chain, not a server.

Audit-ready evidence in 5 lines — and verifiable offline.

· pip install cendor-acttrace

from cendor.core import instrument
from cendor.acttrace import AuditLog

client = instrument(OpenAI())
audit = AuditLog(system="loan_triage", risk_tier="high", signing_key="…")  # auto-subscribes

with audit.decision(input=application, actor="agent") as d:
    resp = client.chat.completions.create(model="gpt-4o", messages=msgs)  # auto-logged
    d.record(model="gpt-4o", prompt_id="triage@v3")          # cost/context captured for free
    d.human_oversight(reviewer="ops@bank", action="approved")

audit.export("evidence_q3.jsonl", framework="eu_ai_act")     # evidence pack (also nist_rmf)

acttrace verify evidence_q3.jsonl --key "…"   # re-walks the chain + checks signatures; non-zero if broken

Highlights

• Auto-populating — construct an AuditLog and it subscribes to the bus: every LLM/tool call, plus cost (tokenguard) and context decisions (contextkit) on the same stream, becomes an entry — no per-call wiring.
• Tamper-evident hash chain — verify() catches edits, reordering, and tail-truncation. The pack's _meta head+count catch truncation, but that header is only authenticated when the log is HMAC-signed and you verify(key=…) — the header itself is signed, so a rewritten _meta fails. Without a key it's an unauthenticated in-file check, so pass an out-of-band expected_head= (captured from log.head at write time) for an authoritative completeness guarantee. Each entry is optionally HMAC-signed too.
• Decisions & oversight — decision() groups a unit of work; d.record(...) and d.human_oversight(reviewer, action) capture Art. 14-style sign-off.
• Compliance evidence packs — export(framework=…) annotates control IDs for EU AI Act, ISO/IEC 42001, GDPR, and NIST AI RMF (starting templates, not certified mappings), and a _meta.summary (counts of decisions, oversight, flags by action/severity) gives a reviewer the at-a-glance read first. PII redaction on by default (swap in redactor=).
• Auto-flag on redaction — when the built-in redactor scrubs PII/secrets (email, api_key incl. sk-ant-/sk-proj-, aws_key, google_api_key, jwt, bearer_token) from an auto-captured entry, acttrace appends a policy_flag recording which category was removed — so "we removed PII" is in the hash chain, not silent (flag_on_redact=True by default; a custom redactor= owns its own flagging).
• Policy flags (validation) — audit.flag(reason, action="blocked", …) records a tamper-evident policy_flag (and returns the chained entry) when your pre-flight guard refuses input that shouldn't be processed — so the refusal is auditable, not just the calls that ran:

from cendor.core.instrument import add_interceptor, MISS

def guard(call):                                    # your pre-flight policy guard
    if my_policy_disallows(call):                   # YOUR rule
        audit.flag("special-category data", action="blocked")   # acttrace records the refusal
        raise PolicyViolation("blocked")            # your guard enforces it
    return MISS

add_interceptor(guard)   # the blocked call never reaches the bus — flag() is its only record

Produces evidence to support compliance — not legal advice, not a guarantee. Control mappings are starting templates for your compliance team.

See docs/acttrace.md · CHANGELOG. Part of the Cendor stack — github.com/cendorhq/Cendor. Powered by PowerAI Labs. Apache-2.0; provided "as is", without warranty — use at your own risk (LICENSE §7–8).