Outpace the adversary. Operate with intelligence.
HACKFORLAB is the operator-grade threat intelligence and hunting platform built for defenders who refuse to wait for tomorrow’s headline. A multi-million ML-filtered indicator catalogue, thousands of tracked adversary clusters, a deep historical archive — engineered for the SOC analyst at 03:00, the threat hunter on a Friday afternoon, and the detection engineer shipping code on Monday.
Cataloged, ML-scored, MITRE-tagged. Refreshed continuously across OSINT, commercial, sandbox, TLS, DNS, and honeynet sources.
Multi-million observations, structured for query
A breakdown of the catalogue by observable type, plus the top MITRE techniques driving current-cycle indicator volume. Every number is queryable in the operator console; every record carries provenance, confidence score, and attribution.
Defenders are losing the time race.
Three structural shifts have rewritten what threat intelligence has to do — and most threat-intelligence programs have not caught up.
Disclosure-to-exploitation has collapsed
In 2024-2025, the average gap between a high-severity CVE disclosure and the first observed mass-scanning campaign dropped below 96 hours. By the time a manual indicator review reaches your SOC, the adversary is already inside.
Supply-chain compromise arrives in waves
In a single calendar week in May 2026, three independent package-registry compromises landed. Multi-month threat reports do not catch wave dynamics. Weekly briefings tied to live indicator deltas do.
Adversaries moved into the cloud control plane
Identity-driven cloud attacks now cross both control plane (CloudTrail, IAM, Kubernetes audit) and data plane (VPC Flow, EDR, DNS) — often in a single kill chain. Single-plane hunting is blind by design.
HACKFORLAB was built on a different premise. Continuously refreshed indicator atoms. Machine-learning filtering to separate real threats from feed noise. MITRE-aligned hunt playbooks that ship with their queries. Detection engineering treated as software, with backtests, false-positive curves, and runbooks attached to every rule. We index what adversaries are doing right now — not what they did last quarter — and we expose it through interfaces a SOC analyst, threat hunter, and detection engineer can each use without translating between tools.
Multi-million indicators across more than thousands of adversary clusters, every observation ML-scored for confidence, MITRE-tagged for technique, geo-tagged for region, CVE-linked when applicable, and attributed to the campaign it belongs to. This is the data layer beneath every published playbook on this site and every dashboard inside the operator console at huntintel.hackforlab.com.
Five steps. Under two hours. First detection candidate by lunch.
No sales call required. Sign in, point at your log sources, and start producing operational output the same day.
Most threat-intelligence platforms have a three-month onboarding cycle that ends with a half-configured deployment. HACKFORLAB is different. The console lands you in the analyst view on the first sign-in. The indicator catalogue is pre-populated with multi-million atoms. The published hunt library is pre-loaded with seven VPC Flow Log playbooks, five cloud-plane playbooks, and twelve detection-engineering patterns. The weekly advisory subscription is one click.
By the end of your first hour, you have searched the catalogue, pivoted from an observed indicator to its adversary cluster, viewed the cluster\’s MITRE technique distribution, and exported a high-confidence indicator subset to your SIEM. By the end of the first session, you have one hunt running against your own log sources and a candidate detection in your triage queue.
Intelligence, hunting, engineering — one platform.
Built around the workflows that real defenders run every day. Not features that sound good in a brochure. Capabilities that show up in your detection coverage, your mean-time-to-detect, and your portfolio of shipped rules.
Threat Intelligence That Operates
A live catalogue of adversary infrastructure, indicator atoms, campaign clusters, and CVE-to-IOC links. Streamed via API, exported to your stack, queryable in the operator console. No more weekly indicator email digests — fresh data, every cycle.
Hunt Playbooks You Can Run Tomorrow
MITRE-aligned hunts for cloud control planes, VPC Flow Logs, identity systems, and Kubernetes. Each ships with a hypothesis, a feature table, the query, a false-positive curve, and a triage runbook. Reading time to operational use: under an hour.
Detection Engineering That Ships
A five-stage detection-as-code pipeline with backtests, FP curves, and runbooks attached to every rule. Manage your portfolio in version control. Promote a successful hunt to a continuous detection via pull request. Retire what no longer earns its keep.
Four seats in the SOC. One console.
Every persona who touches a security platform gets a dedicated workflow tuned to what they actually do.
Tier 2 / 3 SOC analyst
Paste an observed indicator, get a verdict with full context in under sixty seconds. Pivot from one IP to the adversary cluster, the linked campaign, the MITRE technique distribution, and the recommended block list. Annotate, tag, and pivot back into your SIEM seamlessly.
Threat hunter
Run any of 12+ published playbooks against your VPC Flow, CloudTrail, K8s audit, or EDR sources. Hits land in a triage queue with the features that fired, the upstream telemetry, and a verdict template. Promote useful hunts to continuous detections via pull request.
Detection engineer
Manage your rule portfolio as code. Backtests against ninety days of historical telemetry. False-positive curves visible at threshold-tuning time. Unit tests survive every change. Retirement criteria documented per rule. The pipeline behaves like software because it is.
Security leader
A defensible view of your detection portfolio mapped against the live adversary landscape. Weekly briefings short enough for executive consumption. MITRE coverage exports for board reporting. Audit-ready evidence trails on every detection lifecycle event.
How a SOC analyst actually uses the platform.
A walkthrough of one real workflow — from a noisy SIEM alert at 09:14 to a confirmed adversary attribution and shipped detection by lunchtime.
09:14 — Alert lands. SIEM fires on an outbound connection from a production EC2 instance to an unfamiliar IP. The analyst opens the platform\’s IOC Hunting page and pastes the IP. Two seconds later: Verdict — High. Source feeds — 3 corroborating. Severity — Critical. Actor — known commodity botnet operator. MITRE — T1071 (Application Layer Protocol). Related CIDR cluster — 8 sibling IPs observed in the same /24 over the past 14 days.
09:16 — Pivot to cluster. Click the related-CIDR link. Land in Knowledge Graph → CIDR Clusters with the /24 pre-loaded. See every indicator from that range — 47 IPs, 12 domains, 4 file hashes. See every actor associated — 3 named adversary clusters share the range, hinting at a bulletproof-hosting concentration.
09:24 — Profile the operator. Click the primary actor card. The per-actor page shows TTP frequency, geographic targeting, recent activity sparkline, and the campaign lineage. The analyst now knows this is not a one-off — it is part of a campaign that has been escalating for three weeks.
09:42 — Run a hunt. Open the VPC Flow Log hunting series. Run the “Adaptive C2 Beacon Detection (FFT + DBSCAN)” playbook against the same 30-day window. Twelve more hits surface — including three EC2 instances that did not trip the SIEM alert.
10:18 — Triage and contain. Each hit lands in the analyst queue with the FFT periodicity score, the cluster proximity, and the link to the upstream Athena query. The analyst annotates each, marks the three new EC2s as Confirmed-Malicious, and pushes the IP set to the perimeter blocking infrastructure.
11:36 — Ship a detection. The hunt proved useful enough to become a continuous detection. The analyst opens a pull request that promotes the playbook to the detection-as-code repository, attaches the backtest result (90 days, 12 historical hits, 0 false positives at the chosen threshold), and assigns a reviewer.
12:04 — Lunch. What was a single noisy alert is now an investigated incident, a shipped detection, and a contributing observation to next Monday\’s weekly advisory.
Adversaries operate everywhere. So do we.
Indicator origin density across regions, recomputed continuously. The pulse positions surface where adversary infrastructure is concentrating right now — useful for prioritising geographic detection coverage.
Maturity model — and how the platform moves you up.
A four-level model derived from observed program patterns. Most security teams operate at L1 or L2. The platform is designed to move you to L3 in weeks, not quarters.
Most security teams are stuck somewhere between Reactive (L1) and Proactive (L2). The technical foundation exists — they have a SIEM, they ingest indicators, they respond to alerts — but the work is alert-driven and triage-heavy. Detection rules accrete without retirement criteria. Hunting happens on an ad-hoc basis when an executive asks. MITRE alignment is aspirational rather than measured.
Moving to Predictive (L3) requires three capabilities most programs lack today: continuous hunting tied to a hypothesis-and-feature workflow, detection-as-code with backtests and metrics, and live MITRE coverage measurement. The platform supplies all three out of the box. Moving to Adaptive (L4) requires ML-augmented detection with closed-loop scoring — also built in.
A typical engagement: an L2 program adopts the platform on Day 0, ships its first PR-managed detection in Week 1, runs its first ML-scored hunt in Week 2, and publishes its first internal MITRE coverage report in Month 1. That is the L2-to-L3 transition, accelerated by an order of magnitude.
Where the platform connects to your existing stack.
Five integration categories. No proprietary connectors required. Every integration uses open standards or REST.
Operational metrics customers report after the first 90 days.
From “what is this IP?” to a full verdict with attribution, cluster, MITRE technique, and CVE link.
ML-filtered indicator scoring eliminates the long tail of low-confidence feed noise that drives alert fatigue.
MITRE-mapped, query-attached, false-positive-curve-documented. Run against your own log sources.
Named profiles built from observed indicator atoms, refreshed continuously.
Operator-level answers, not marketing answers.
How does HACKFORLAB filter real threats from feed noise?
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How fresh is the indicator catalogue?
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Where does the data come from?
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Can we run hunts on our own telemetry without sharing it externally?
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How does this integrate with our existing SIEM and SOAR?
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Is this competitive with our existing threat-intel vendor?
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What does a typical first hour on the platform look like?
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How do you handle false positives?
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Do you support MITRE ATT&CK navigator export?
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How is access controlled?
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How do we get started?
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What about compliance and audit requirements?
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Twelve playbooks that ship with the queries attached.
Each hunt is a hypothesis, a feature table, a pre-processing query, and a scoring layer — peer-reviewed, backtested, ready to run. No “what should I look for” prose. Run them today.
Adaptive C2 Beacon Detection
FFT and DBSCAN for periodicity extraction with jitter modelling on VPC Flow Logs. Targets MITRE T1071.
Low-and-Slow Exfiltration
Isolation Forest plus LSTM seasonality modelling for stealthy data exfiltration over established sessions. Targets T1041.
Lateral Movement Graphs
Graph analytics on VPC Flow Logs with identity-aware east-west traversal and anomalous principal-edge weighting. Targets T1021.
TLS Fingerprinting (JA3/JA4/JARM)
Fingerprint clustering for encrypted C2 hunting. Categorise tooling by fingerprint family.
DGA + DNS-Tunnel Hunting
Entropy and n-gram models on resolved domains. Detection of DNS-tunnelled C2 in cloud DNS metadata.
Living-off-the-Cloud Chain
CloudTrail and VPC Flow fusion to detect cloud-native LotL kill chains end-to-end.
What we will tell your security review team.
Data residency
Customer telemetry stays in customer cloud account. Athena query plane runs in your AWS account. Platform never copies raw telemetry to its own infrastructure.
Authentication
SAML SSO supported. Three-tier RBAC: Analyst, Hunter, Admin. Role escalation forbidden by design. PII tokenisation enforced at ingest.
Audit trail
Every action logged with full attribution. Exportable, retention configurable per tenant. Supports compliance frameworks requiring demonstrable access-control evidence.
Encryption
TLS 1.3 in transit. AES-256 at rest. HSM-backed key management. Per-tenant key isolation. Cipher suites rotated quarterly.
Vulnerability response
Bug bounty program. Coordinated disclosure window. Critical CVE patch SLA: 24 hours. Quarterly third-party penetration testing.
Sub-processor list
Maintained publicly. Material changes notified 30 days in advance. DPA available on request. SOC 2 Type 2 audit in progress.
Four differentiators that matter in the field.
Built by defenders, for defenders
Every playbook on this site was used in production before it was published. The methodology is what we actually run, not what we wish we ran. The engineers who built the platform have shipped detections for global SOCs and incident response teams.
Indicator atoms, not narratives
You get observed infrastructure with provenance, confidence, and timestamps — not vendor prose. Plug it directly into detection. The catalogue is queryable, exportable, and tagged with enough metadata for downstream automation.
ML-filtered, MITRE-aligned end to end
Every IOC, every hunt, every detection is ML-scored and tagged against ATT&CK. Your portfolio against the live threat landscape is one click away. Coverage gaps are visible. Investment priorities are computable.
Detection-as-code first
The pipeline is engineered. Rules ship via PR with backtests, FP curves, runbooks. Retire what no longer earns its keep. This is software engineering applied to detection — versioned, tested, reviewed, deployable, retirable.
Stop reading about threats. Start hunting them.
Sign in to query multi-million ML-filtered indicators, run MITRE-mapped hunts against your own log sources, subscribe to the weekly advisory, and manage your detection portfolio as code. No sales call required for first-session value.
