Generate, export, load, and verify forensic evidence from GitHub sources. Use when creating verifiable evidence objects from GitHub API, GH Archive, Wayback Machine, local git repositories, or security vendor reports. Handles evidence storage, querying, and re-verification against original sources.
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Purpose: Create, store, and verify forensic evidence from GitHub-related public sources and local git repositories.
from src.collectors import GitHubAPICollector, LocalGitCollector, GHArchiveCollector
from src import EvidenceStore
# Create collectors for different sources
github = GitHubAPICollector()
local = LocalGitCollector("/path/to/repo")
archive = GHArchiveCollector()
# Collect evidence from GitHub API
commit = github.collect_commit("aws", "aws-toolkit-vscode", "678851b...")
pr = github.collect_pull_request("aws", "aws-toolkit-vscode", 7710)
# Collect evidence from local git (first-class forensic source)
local_commit = local.collect_commit("HEAD")
dangling = local.collect_dangling_commits() # Forensic gold!
# Store and export
store = EvidenceStore()
store.add(commit)
store.add(pr)
store.add(local_commit)
store.add_all(dangling)
store.save("evidence.json")
# Verify all evidence against original sources
is_valid, errors = store.verify_all()Collects evidence from the live GitHub API.
from src.collectors import GitHubAPICollector
collector = GitHubAPICollector()| Method | Returns |
|---|---|
collect_commit(owner, repo, sha) | CommitObservation |
collect_issue(owner, repo, number) | IssueObservation |
collect_pull_request(owner, repo, number) | IssueObservation |
collect_file(owner, repo, path, ref) | FileObservation |
collect_branch(owner, repo, branch_name) | BranchObservation |
collect_tag(owner, repo, tag_name) | TagObservation |
collect_release(owner, repo, tag_name) | ReleaseObservation |
collect_forks(owner, repo) | list[ForkObservation] |
Collects evidence from local git repositories. Essential for forensic analysis of cloned repos.
from src.collectors import LocalGitCollector
collector = LocalGitCollector("/path/to/cloned/repo")
# Collect a specific commit
commit = collector.collect_commit("HEAD")
commit = collector.collect_commit("abc123")
# Find dangling commits (not reachable from any ref)
# This is forensic gold - reveals force-pushed or deleted commits!
dangling = collector.collect_dangling_commits()
for commit in dangling:
print(f"Found dangling: {commit.sha[:8]} - {commit.message}")| Method | Returns |
|---|---|
collect_commit(sha) | CommitObservation |
collect_dangling_commits() | list[CommitObservation] |
Collects and recovers evidence from GH Archive (BigQuery). Requires credentials.
from src.collectors import GHArchiveCollector
collector = GHArchiveCollector()
# Query events by timestamp (YYYYMMDDHHMM format)
events = collector.collect_events(
timestamp="202507132037",
repo="aws/aws-toolkit-vscode"
)
# Recover deleted content
deleted_issue = collector.recover_issue("aws/aws-toolkit-vscode", 123, "2025-07-13T20:30:24Z")
deleted_pr = collector.recover_pr("aws/aws-toolkit-vscode", 7710, "2025-07-13T20:30:24Z")
deleted_commit = collector.recover_commit("aws/aws-toolkit-vscode", "678851b", "2025-07-13T20:30:24Z")
force_pushed = collector.recover_force_push("aws/aws-toolkit-vscode", "2025-07-13T20:30:24Z")| Method | Returns |
|---|---|
collect_events(timestamp, repo, actor, event_type) | list[Event] |
recover_issue(repo, number, timestamp) | IssueObservation |
recover_pr(repo, number, timestamp) | IssueObservation |
recover_commit(repo, sha, timestamp) | CommitObservation |
recover_force_push(repo, timestamp) | CommitObservation |
Collects archived snapshots from the Wayback Machine.
from src.collectors import WaybackCollector
collector = WaybackCollector()
# Get all snapshots for a URL
snapshots = collector.collect_snapshots("https://github.com/owner/repo")
# With date filtering
snapshots = collector.collect_snapshots(
"https://github.com/owner/repo",
from_date="20250101",
to_date="20250731"
)
# Fetch actual content of a snapshot
content = collector.collect_snapshot_content(
"https://github.com/owner/repo",
"20250713203024" # YYYYMMDDHHMMSS format
)Verification is separated from data collection. Use ConsistencyVerifier to validate evidence against original sources.
from src.verifiers import ConsistencyVerifier
verifier = ConsistencyVerifier()
# Verify single evidence
result = verifier.verify(commit)
if not result.is_valid:
print(f"Errors: {result.errors}")
# Verify multiple
result = verifier.verify_all([commit, pr, issue])Or use the convenience method on EvidenceStore:
store = EvidenceStore()
store.add_all([commit, pr, issue])
is_valid, errors = store.verify_all()Store, query, and export evidence collections.
from src import EvidenceStore
from datetime import datetime
store = EvidenceStore()
# Add evidence
store.add(commit)
store.add_all([pr, issue, ioc])
# Query
commits = store.filter(observation_type="commit")
recent = store.filter(after=datetime(2025, 7, 1))
from_github = store.filter(source="github")
from_git = store.filter(source="git")
repo_events = store.filter(repo="aws/aws-toolkit-vscode")
# Export/Import
store.save("evidence.json")
store = EvidenceStore.load("evidence.json")
# Summary
print(store.summary())
# {'total': 5, 'events': {...}, 'observations': {...}, 'by_source': {...}}
# Verify all against sources
is_valid, errors = store.verify_all()from src import load_evidence_from_json
import json
with open("evidence.json") as f:
data = json.load(f)
for item in data:
evidence = load_evidence_from_json(item)
# Evidence is now a typed Pydantic modelAll 12 GitHub event types are supported:
| Type | Description |
|---|---|
| PushEvent | Commits pushed |
| PullRequestEvent | PR opened/closed/merged |
| IssueEvent | Issue opened/closed |
| IssueCommentEvent | Comment on issue/PR |
| CreateEvent | Branch/tag created |
| DeleteEvent | Branch/tag deleted |
| ForkEvent | Repository forked |
| WatchEvent | Repository starred |
| MemberEvent | Collaborator added/removed |
| PublicEvent | Repository made public |
| ReleaseEvent | Release published/created/deleted |
| WorkflowRunEvent | GitHub Actions run |
| Type | Description | Sources |
|---|---|---|
| CommitObservation | Commit metadata and files | GitHub, Git, GH Archive |
| IssueObservation | Issue or PR | GitHub, GH Archive |
| FileObservation | File content at ref | GitHub |
| BranchObservation | Branch HEAD | GitHub |
| TagObservation | Tag target | GitHub |
| ReleaseObservation | Release metadata | GitHub |
| ForkObservation | Fork relationship | GitHub |
| SnapshotObservation | Wayback snapshots | Wayback |
| IOC | Indicator of Compromise | Vendor |
| ArticleObservation | Security report/blog | Vendor |
from src import EvidenceSource, IOCType
from src.schema import IOC, VerificationInfo
from pydantic import HttpUrl
from datetime import datetime, timezone
# IOCs are created directly as schema objects
ioc = IOC(
evidence_id="ioc-commit-sha-abc123",
observed_when=datetime.now(timezone.utc),
observed_by=EvidenceSource.SECURITY_VENDOR,
observed_what="Malicious commit SHA found in vendor report",
verification=VerificationInfo(
source=EvidenceSource.SECURITY_VENDOR,
url=HttpUrl("https://vendor.com/report")
),
ioc_type=IOCType.COMMIT_SHA,
value="678851bbe9776228f55e0460e66a6167ac2a1685",
)Available IOC types: COMMIT_SHA, FILE_PATH, FILE_HASH, CODE_SNIPPET, EMAIL, USERNAME, REPOSITORY, TAG_NAME, BRANCH_NAME, WORKFLOW_NAME, IP_ADDRESS, DOMAIN, URL, API_KEY, SECRET
cd .claude/skills/oss-forensics/github-evidence-kit
pip install -r requirements.txt
pytest tests/ -v --ignore=tests/test_integration.pyIntegration tests hit real external services (GitHub API, BigQuery, vendor URLs):
# All integration tests
pytest tests/test_integration.py -v -m integration
# Skip integration tests in CI
pytest tests/ -v -m "not integration"Note: GitHub API integration tests use 60 req/hr unauthenticated rate limit. BigQuery tests require credentials (see below).
GH Archive queries require Google Cloud BigQuery credentials. Two options:
export GOOGLE_APPLICATION_CREDENTIALS=/path/to/credentials.jsonUseful for .env files or CI secrets:
export GOOGLE_APPLICATION_CREDENTIALS='{"type":"service_account","project_id":"...","private_key":"..."}'The client auto-detects JSON content vs file path.
BigQuery User roleGOOGLE_APPLICATION_CREDENTIALS env varFree Tier: 1 TB/month of BigQuery queries included.
pip install -r requirements.txtpydantic - Schema validationrequests - HTTP clientgoogle-cloud-bigquery - GH Archive queries (optional)google-auth - GCP authentication (optional)75f6956
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