Listen to this Post
Introduction:
Bug bounty platforms like HackerOne promise to bridge ethical hackers with organizations, but a recent incident with ClickUp exposed a fatal flaw: triage failures. In April 2025, ClickUp suffered a data leak directly attributed to HackerOne’s triage team closing a critical report — containing 893 exposed emails and a live API token — as a “duplicate” twice. This wasn’t a one-off; it happened at least three times. When automated or analyst-driven triage auto-closes valid findings as “informative” or duplicate, real vulnerabilities fester, turning bug bounties into a false sense of security.
Learning Objectives:
- Identify common triage failure patterns (duplicate misclassification, “too many steps” rejection, AI‑overconfidence).
- Implement a secondary internal review workflow to override external platform decisions.
- Automate detection and revocation of exposed API tokens using open‑source tools and cloud hardening techniques.
You Should Know
- Detecting Exposed API Tokens in Public & Private Repos (Before Attackers Do)
The ClickUp leak included a live API token — a direct vector for data exfiltration. To prevent this, regularly scan your codebase and CI/CD logs.
Step‑by‑Step Guide (Linux / macOS / WSL):
1. Install Gitleaks (detects secrets in git history):
docker run --rm -v $(pwd):/path zricethezav/gitleaks:latest detect --source=/path --verbose
Or natively:
brew install gitleaks macOS sudo apt install gitleaks Debian/Ubuntu gitleaks detect --source=. --redact
2. Use TruffleHog (entropy‑based scanning):
docker run -it -v "$PWD:/pwd" trufflesecurity/trufflehog:latest github --repo=https://github.com/yourorg/yourrepo --json
- For Windows (PowerShell), run TruffleHog via Docker Desktop:
docker run -it -v ${PWD}:/pwd trufflesecurity/trufflehog:latest filesystem /pwd --regex
4. Automate pre‑commit hooks to block tokens:
pip install pre-commit pre-commit install
Add to `.pre-commit-config.yaml`:
- repo: https://github.com/zricethezav/gitleaks rev: v8.18.0 hooks: - id: gitleaks
What this does: Scans all committed files, history, and secrets entropy to catch API keys, tokens, and credentials before they leak — exactly the type HackerOne’s triage missed.
2. Automating Triage Validation to Prevent “Duplicate” Closures
HackerOne closed the critical report as a duplicate twice. You can build an internal bot that checks incoming reports against your own vulnerability database.
Step‑by‑Step using Python + Jira/API:
- Export your internal finding database (e.g., CSV of previous reports).
- Script to compare new reports (using fuzzy matching on title/description):
from difflib import SequenceMatcher</li> </ol> def is_duplicate(new_title, existing_titles, threshold=0.85): for old in existing_titles: if SequenceMatcher(None, new_title.lower(), old.lower()).ratio() > threshold: return True return False
3. Webhook receiver to catch HackerOne report creations (or manual CSV upload):
Using ngrok to expose local webhook ngrok http 5000
4. Auto‑escalate if duplicate score > threshold but severity is Critical/High → force human review.
5. Linux cron job to poll HackerOne’s GraphQL API for new reports (requires OAuth token):curl -X POST https://api.hackerone.com/v1/graphql \ -H "Authorization: Bearer $H1_TOKEN" \ -H "Content-Type: application/json" \ -d '{"query":"query { me { reports { edges { node { title severity state } } } } }"}' | jq '.'Why this matters: No external triage (AI or human) replaces your internal context. This script ensures no critical vuln gets buried as “duplicate.”
3. ClickUp‑Style API Token Hardening & Revocation Playbook
The leaked token gave attackers access to ClickUp’s workspace. Implement these mitigations immediately.
Windows / Linux / Cloud (AWS/Azure/GCP) Steps:
- Never hardcode tokens – use environment variables or secrets manager.
– Linux: `export CLICKUP_API_KEY=”your_key”` (never in
.bash_history).
– Windows (CMD): `setx CLICKUP_API_KEY “your_key” /M` (restrict permissions).
2. Rotate tokens automatically – AWS Secrets Manager example:aws secretsmanager rotate-secret --secret-id clickup-token --rotation-rules AutomaticallyAfterDays=30
3. Implement token scope restrictions (ClickUp supports granular permissions):
– Generate tokens with read‑only or limited workspace scope.
– Regularly audit via `curl -H “Authorization: Bearer $TOKEN” https://api.clickup.com/api/v2/team` – if it returns more than necessary, revoke.
4. Use a proxy + vault (Hashicorp Vault on Linux):vault kv put secret/clickup api_key=$CLICKUP_API_KEY vault read -field=api_key secret/clickup | your_script
5. Monitor for anomalous API calls – set up CloudTrail (AWS) or Azure Monitor alert on new IPs / high volume.
Recovery command after a leak (revoke all tokens):
ClickUp API bulk revocation (if supported) curl -X POST https://api.clickup.com/api/v2/token/revoke \ -H "Authorization: Bearer $LEAKED_TOKEN" \ -H "Content-Type: application/json" \ -d '{"revoke_all": true}'- Building a Redundant Triage Process with Internal Secondary Review
HackerOne’s failure stemmed from single‑point triage. Add a “four‑eyes” principle.
Step‑by‑Step via Jira Automation + Slack:
- Create a Jira “Bug Bounty Review” project with custom fields: External Platform, Report ID, Severity Override.
- Automation rule triggered by HackerOne webhook (via Zapier or custom Lambda):
– New report → create Jira ticket → assign to two internal analysts.
– Both must approve severity before closure.
3. If discrepancy (one marks duplicate, other critical) → auto‑escalate to security lead.
4. Slack alert for any “duplicate” closure on Critical/High:curl -X POST -H 'Content-type: application/json' \ --data '{"text":"H1 Report 123 closed as duplicate — override possible?"}' \ https://hooks.slack.com/services/YOUR/WEBHOOK5. Linux script to monitor HackerOne’s public activity (rate‑limited):
while true; do curl -s https://hackerone.com/clickup/activity | grep -i "closed|duplicate" sleep 300 done
Result: Even if HackerOne’s team fails, your internal secondary review catches the mistake before data leaks.
- Simulating a “Duplicate Closure” Attack (for Blue Team Training)
To test your triage robustness, run a red‑team exercise that mimics the ClickUp scenario.
Using Burp Suite + custom Python script:
- Find a real low‑severity issue (e.g., missing security header).
- Report it via a fake researcher account to your own bug bounty program (if self‑hosted).
- Wait for triage to close as “duplicate” (or informational).
- Then submit a second report for the same endpoint but with a working exploit for a critical API token leak.
- Measure if the triage process (human or AI) auto‑closes it based on endpoint similarity.
- Generate a proof‑of‑concept script to demonstrate token extraction:
!/bin/bash Fake POC for training echo "Extracting token from ClickUp API via misconfigured CORS..." curl -X GET "https://api.clickup.com/api/v2/user" -H "Authorization: Bearer DUMMY_TOKEN"
Linux command to compare timestamps of duplicate closures:
Log all closure events jq '.data.reports.edges[].node.closedAt' h1_reports.json | sort
Mitigation: Implement a rule that any duplicate closure on a previously reported endpoint requires manual override if the new severity is higher.
6. Monitoring HackerOne’s Own Triage Performance via GraphQL
Don’t trust platform metrics; build your own dashboard.
Step‑by‑Step API Monitoring:
- Obtain HackerOne API token (under Settings → API).
- Query all your program’s reports for the last 90 days:
curl -X POST https://api.hackerone.com/v1/graphql \ -H "Authorization: Bearer $H1_TOKEN" \ -H "Content-Type: application/json" \ -d '{"query":"query { program(handle: \"your_program\") { reports(first: 100, filter: { state: [\"closed\"] }) { edges { node { title severity state triaged_by { username } closed_reason } } } } }"}' > reports.json - Parse for “duplicate” closures where severity = Critical:
jq '.data.program.reports.edges[] | select(.node.closed_reason == "duplicate" and .node.severity == "critical")' reports.json
- Alert if count > 0 within 7 days → trigger internal audit.
5. Windows PowerShell alternative:
$body = @{query = "..."} | ConvertTo-Json Invoke-RestMethod -Uri "https://api.hackerone.com/v1/graphql" -Method Post -Body $body -Headers @{Authorization = "Bearer $env:H1_TOKEN"}What you learn: HackerOne triage doesn’t re‑evaluate duplicates when new information appears — you need this API polling to catch their mistake.
- Cloud Hardening for API‑Driven Workspaces (ClickUp, Notion, Slack)
The leaked token gave attackers full access. Implement zero‑trust for third‑party integrations.
AWS / Azure / GCP Commands (Linux):
1. Enforce short‑lived tokens using AWS STS:
aws sts assume-role --role-arn "arn:aws:iam::123456789012:role/ClickUpIntegration" --role-session-name "temp-token" --duration-seconds 3600
2. Use VPC endpoint policies to restrict ClickUp API calls only from your IP ranges:
Example AWS VPC endpoint policy aws ec2 create-vpc-endpoint --vpc-id vpc-abc123 --service-name com.amazonaws.us-east-1.execute-api --policy-document '{"Statement":[{"Action":"execute-api:Invoke","Effect":"Allow","Principal":"","Resource":"","Condition":{"IpAddress":{"aws:SourceIp":"203.0.113.0/24"}}}]}'3. Automate token revocation on anomaly – AWS Lambda + Slack webhook:
def revoke_token(event, context): Check CloudTrail for unusual API calls Call ClickUp's revoke endpoint requests.post("https://api.clickup.com/api/v2/token/revoke", headers={"Authorization": f"Bearer {os.getenv('LEAKED_TOKEN')}"})4. Windows (Azure): Use Managed Identity and Key Vault access policies to avoid long‑lived secrets.
Post‑leak cleanup command (Linux):
grep -r "clickup_api_key" /etc/ /home/ 2>/dev/null | cut -d: -f1 | xargs sed -i 's/clickup_api_key=./clickup_api_key=REVOKED/g'
What Undercode Say
- Key Takeaway 1: No bug bounty platform can replace internal secondary review. HackerOne’s “duplicate” failures prove that automation and overworked analysts will miss critical findings — always maintain an independent validation workflow.
- Key Takeaway 2: Exposed API tokens are the new ransomware vector. Implementing automated scanning (Gitleaks/TruffleHog), short‑lived credentials, and real‑time revocation can stop a leak from becoming a breach, even when triage fails.
Analysis: The ClickUp incident isn’t an outlier — it’s a systemic flaw in how external bug bounty platforms prioritize throughput over accuracy. HackerOne’s AI or analysts auto‑close valid reports as “informative” or duplicate, driven by metrics like time‑to‑close. Meanwhile, attackers index every public report. The solution isn’t ditching HackerOne (though that helps); it’s building a fail‑safe layer inside your own SOC. The commands and scripts above transform your team from passive recipients of triage decisions to active guardians. You must log, alert, and override — or you’re next.
Prediction: Within 12 months, major enterprises will mandate “triage‑override SLAs” in bug bounty contracts, requiring platforms like HackerOne to provide raw data dumps for internal correlation. We’ll see a rise of hybrid models: automated triage for low/medium, but all Critical/High reports must be reviewed by both platform and customer security teams simultaneously. AI‑only triage will be abandoned after 3–4 more public breaches. The companies that survive will be those that treat bug bounties as intelligence feeds, not security guarantees.
▶️ Related Video (68% Match):
🎯Let’s Practice For Free:
IT/Security Reporter URL:
Reported By: Souhaib Naceri – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅🔐JOIN OUR CYBER WORLD [ CVE News • HackMonitor • UndercodeNews ]
📢 Follow UndercodeTesting & Stay Tuned:
