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klingai-audit-logging

klingai-audit-logging

Implement audit logging for Kling AI operations for compliance and security. Use when tracking API usage or preparing for audits. Trigger with phrases like 'klingai audit', 'kling ai audit log', 'klingai compliance log', 'video generation audit trail'.

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill 문서

GitHub

name: klingai-audit-logging description: 'Implement audit logging for Kling AI operations for compliance and security. Use when tracking

API usage or preparing for audits. Trigger with phrases like ''klingai audit'', ''kling ai audit log'',

''klingai compliance log'', ''video generation audit trail''.

' allowed-tools: Read, Write, Edit, Bash(npm:*), Grep version: 1.18.0 license: MIT author: Jeremy Longshore jeremy@intentsolutions.io tags:

  • saas
  • kling-ai
  • audit
  • compliance
  • logging compatibility: Designed for Claude Code

Kling AI Audit Logging

Overview

Compliance-grade audit logging for Kling AI API operations. Every task submission, status change, and credential usage is captured in tamper-evident structured logs.

Audit Event Schema

import json
import hashlib
import time
from datetime import datetime
from pathlib import Path

class AuditLogger:
    """Append-only audit log with integrity checksums."""

    def __init__(self, log_dir: str = "audit"):
        self.log_dir = Path(log_dir)
        self.log_dir.mkdir(exist_ok=True)
        self._prev_hash = "genesis"

    def _compute_hash(self, entry: dict) -> str:
        raw = json.dumps(entry, sort_keys=True) + self._prev_hash
        return hashlib.sha256(raw.encode()).hexdigest()[:16]

    def log(self, event_type: str, actor: str, details: dict):
        """Write a tamper-evident audit entry."""
        entry = {
            "timestamp": datetime.utcnow().isoformat() + "Z",
            "event_type": event_type,
            "actor": actor,
            "details": details,
            "prev_hash": self._prev_hash,
        }
        entry["hash"] = self._compute_hash(entry)
        self._prev_hash = entry["hash"]

        date = datetime.utcnow().strftime("%Y-%m-%d")
        filepath = self.log_dir / f"audit-{date}.jsonl"
        with open(filepath, "a") as f:
            f.write(json.dumps(entry) + "\n")

        return entry["hash"]

Audit Events for Kling AI

class KlingAuditClient:
    """Kling client with full audit trail."""

    def __init__(self, base_client, audit: AuditLogger, actor: str = "system"):
        self.client = base_client
        self.audit = audit
        self.actor = actor

    def text_to_video(self, prompt: str, **kwargs):
        # Log submission
        self.audit.log("task_submitted", self.actor, {
            "action": "text_to_video",
            "model": kwargs.get("model", "kling-v2-master"),
            "duration": kwargs.get("duration", 5),
            "mode": kwargs.get("mode", "standard"),
            "prompt_hash": hashlib.sha256(prompt.encode()).hexdigest()[:16],
            "prompt_length": len(prompt),
        })

        result = self.client.text_to_video(prompt, **kwargs)

        # Log completion
        self.audit.log("task_completed", self.actor, {
            "action": "text_to_video",
            "status": "succeed",
            "video_count": len(result.get("videos", [])),
        })

        return result

    def log_auth_event(self, event: str, success: bool):
        self.audit.log("auth_event", self.actor, {
            "event": event,
            "success": success,
            "access_key_prefix": self.client.config.access_key[:8] + "...",
        })

Audit Log Verification

def verify_audit_chain(log_file: str) -> bool:
    """Verify tamper-evidence of audit log chain."""
    prev_hash = "genesis"
    entries = []

    with open(log_file) as f:
        for line_num, line in enumerate(f, 1):
            entry = json.loads(line)
            entries.append(entry)

            if entry["prev_hash"] != prev_hash:
                print(f"Chain broken at line {line_num}: "
                      f"expected prev_hash={prev_hash}, got {entry['prev_hash']}")
                return False

            # Recompute hash
            check_entry = {k: v for k, v in entry.items() if k != "hash"}
            raw = json.dumps(check_entry, sort_keys=True) + prev_hash
            expected_hash = hashlib.sha256(raw.encode()).hexdigest()[:16]

            if entry["hash"] != expected_hash:
                print(f"Hash mismatch at line {line_num}")
                return False

            prev_hash = entry["hash"]

    print(f"Verified {len(entries)} entries -- chain intact")
    return True

Audit Report Generator

def generate_audit_report(log_dir: str = "audit", days: int = 30) -> dict:
    """Generate compliance audit report."""
    from collections import Counter
    from datetime import timedelta

    log_path = Path(log_dir)
    events = []

    cutoff = datetime.utcnow() - timedelta(days=days)
    for filepath in sorted(log_path.glob("audit-*.jsonl")):
        with open(filepath) as f:
            for line in f:
                entry = json.loads(line)
                if entry["timestamp"] >= cutoff.isoformat():
                    events.append(entry)

    event_types = Counter(e["event_type"] for e in events)
    actors = Counter(e["actor"] for e in events)

    report = {
        "period_days": days,
        "total_events": len(events),
        "event_types": dict(event_types),
        "unique_actors": len(actors),
        "actors": dict(actors),
        "first_event": events[0]["timestamp"] if events else None,
        "last_event": events[-1]["timestamp"] if events else None,
    }

    print(f"\n=== Audit Report ({days} days) ===")
    print(f"Total events: {report['total_events']}")
    for event_type, count in event_types.most_common():
        print(f"  {event_type}: {count}")
    print(f"Actors: {', '.join(actors.keys())}")

    return report

Compliance Checklist

  • All API calls logged with timestamp, actor, action
  • Prompts stored as hashes (not plaintext) for privacy
  • Audit chain integrity verifiable
  • Logs retained for required period (typically 1-7 years)
  • Log access restricted to authorized personnel
  • Regular verification of chain integrity

Prerequisites

  • An approved audit schema, authorized workspace, redaction standard, retention schedule, least-privilege reader roles, synthetic test event, and an incident/rollback owner.

Instructions

  1. Emit append-only, aggregate or hashed audit events; never store prompts, asset URLs, identities beyond approved pseudonymous references, or credentials.
  2. Validate chain integrity, access controls, retention, deletion, policy/rights review, and draft-only workflow events using a sandbox fixture.
  3. Halt exports or access changes on integrity, scope, policy, or retention drift; revoke temporary roles and restore the prior audit configuration.
  4. Promote only after owner approval and retain a redacted verification receipt for the approved window.

Output

Produce an audit receipt with environment, event classes, integrity/access checks, redaction and retention/deletion outcomes, policy/rights and draft-only assertions, owner approval, and rollback reference. Exclude event payloads, prompts, assets, and secrets.

Error Handling

ConditionResponse
Integrity or access control failsStop audit delivery, revoke temporary access, and restore the last verified configuration.
Sensitive data reaches the logQuarantine and delete the affected record, correct redaction, and document only the redacted incident.

Examples

env=staging; events=hashed-aggregate; integrity=pass; access=least-privilege; retention=30d; draft-only=pass; rollback=available is a valid audit check.

Resources

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