AI-Driven Cyber Threat Intelligence (CTI)
Spharaka unifies multi-source threat intelligence and applies AI to enrich, correlate, and operationalise IOCs and IOAs across the AI SOC. Turn raw feeds into context-aware autonomous defence.
Multi-Source Threat Intelligence, Operationalised
Spharaka aggregates open-source, commercial, sector ISAC, and government threat feeds, then enriches every signal with environment-specific context.
- CTI integration with commercial and open-source feeds
- Multi-source threat intelligence fusion and deduplication
- Threat feed correlation across AI SIEM and autonomous response signals
- IOC enrichment with reputation, geo, ASN, and adversary attribution
- Malware intelligence including family, campaign, and capability data
- Vulnerability intelligence linked to assets and exposure
- Reputation intelligence for domains, IPs, files, and identities
- Threat context enrichment for every security event
- Automated IOC matching across historical and live telemetry
Native to the AI SOC
CTI is built into AI SIEM, AI SOAR, AI UEBA, and Autonomous Threat Hunting, so threat intelligence shapes every detection and response decision.
- Retroactive IOC sweeps across historical telemetry
- Automated playbook triggers from new intelligence
- Adversary-aware threat hunting hypotheses
- Customer-isolated CTI memory for organisation-specific context
From a feed to something that changes a decision
Most threat intelligence programmes buy feeds and stop. The value is not in the feed, it is in the four steps after it, and those are the ones that are usually missing.
Ingest
Commercial feeds, open-source sources, sector sharing communities and internal findings arrive continuously in different formats, at different confidence levels, with different definitions of what an indicator means. All of it lands in one place.
Deduplicate and reconcile
The same indicator arrives from five sources with three verdicts and two expiry dates. Reconciling that is unglamorous and it is where most of the noise is removed: one indicator, one record, a confidence derived from who says what and how recently.
Score for this environment
An indicator's importance is not a property of the indicator. A vulnerability in software you do not run and a campaign targeting a sector you are not in are both accurate and both irrelevant. Relevance is scored against your assets, your exposure and your sector.
Attach to the events it bears on
Enrichment happens at ingest, on the specific events the intelligence relates to, rather than being available in a separate portal for an analyst to go and consult. Intelligence that requires a context switch is intelligence that does not get used under load.
Feed detection and hunting
Campaign and technique intelligence generates hunting hypotheses, and confirmed patterns become standing detections. This is the loop that turns a subscription into coverage rather than into a reading list.
Retire
Indicators expire, infrastructure is reassigned, and an IP that hosted a command server last year now hosts a customer. Ageing intelligence out is as important as taking it in, and it is the step most programmes never build.
What comes in, and what it attaches to
Breadth of sourcing matters less than what happens to the intelligence once it arrives.
Intelligence types
- Indicators: domains, IPs, hashes, URLs and certificates
- Malware family, capability and campaign attribution
- Adversary tradecraft mapped to MITRE ATT&CK
- Vulnerability intelligence with exploitation status
- Reputation data for domains, addresses, files and identities
- Sector-specific and regional threat reporting
What it is scored against
- Asset inventory and what is actually exposed
- Software and version inventory, for vulnerability relevance
- Sector, geography and regulatory context
- Existing detections, to find coverage gaps
- Historical telemetry, to check for prior contact
Where it is applied
- Event enrichment at ingest inside AI SIEM
- Case context during autonomous investigation
- Hunting hypotheses for campaigns active in your sector
- Vulnerability prioritisation by real exploitation
- Blocking decisions, bounded by AirWatch policy
Retrospective matching matters as much as live blocking: when an indicator arrives, the platform checks whether the estate contacted it in the past, which is frequently how an intrusion is first discovered.
Operationalised intelligence against a feed subscription
The difference between a CTI programme that changes outcomes and one that produces a weekly report nobody reads.
| Aspect | Feed subscription | Spharaka |
|---|---|---|
| Where it lives | In a threat intelligence platform an analyst opens deliberately, usually after they already suspect something. | Attached to the events it bears on, at ingest, so it is present before anyone thinks to look for it. |
| Duplicate indicators | Five sources, five records, conflicting verdicts, and an analyst reconciling by hand under time pressure. | Fused into one record with a confidence derived from source agreement and recency. |
| Relevance | Everything arrives at the same weight, so the volume itself becomes a reason not to read it. | Scored against your assets and exposure, so a vulnerability in software you do not run does not compete for attention. |
| New indicators | Applied going forward. Whether the estate contacted the infrastructure last month is a separate manual exercise. | Matched retrospectively against history as well as prospectively, which is often how the intrusion is found. |
| Expiry | Rarely managed, so stale indicators accumulate and eventually block something the business needs. | Aged out on confidence and recency, because an address that hosted malware last year may host a customer now. |
| Effect on detection | A report. Turning it into a detection is a project somebody has to schedule. | Campaign tradecraft becomes hunting hypotheses and standing detections without a separate project. |
An indicator that mattered because of what it matched in the past
A commodity indicator arrives from a sector sharing community. Blocking it takes a second and is almost worthless; the value is entirely in the retrospective check.
A domain associated with an initial-access broker is published by a sector sharing group, with medium confidence and no further context.
Two commercial feeds already hold the domain at lower confidence. Agreement across three independent sources raises it, and the record becomes one entry rather than three.
The associated campaign targets financial services through remote access software the organisation runs. Relevance is high, where it would have been near zero for a manufacturer without that software.
The domain is added to blocking under AirWatch policy for this confidence and this category. Roughly a second of work and no evidence anyone was going to contact it.
History is checked. Two hosts resolved the domain nineteen days ago, within a window the incumbent tooling had already aged out of its searchable retention.
Both hosts become cases. One shows a remote access session that was never in a ticket, and the intrusion is dated nineteen days earlier than anyone would otherwise have believed.
The block was the cheap part and would have prevented nothing. The nineteen-day-old match is the finding, and it is only available to a platform that keeps history queryable and checks new intelligence against it automatically.
What to ask about threat intelligence
Feed counts are the wrong metric. These four questions are about what happens after the feed arrives.
Does a new indicator search the past?
Ask what happens when an indicator arrives today. Prospective blocking is table stakes and prevents little. Automatic retrospective matching against retained telemetry is where intrusions are actually discovered.
How is a conflict resolved?
Give it an indicator two sources disagree about. How the platform reconciles confidence, and whether an analyst can see why, decides whether the enrichment can be trusted when it matters.
Show me an indicator that was retired
Stale intelligence eventually blocks something the business needs, and that outage is remembered for years. A platform with no expiry story is accumulating a problem rather than managing one.
Where does the intelligence appear?
If the answer is a portal, it will not be consulted during a busy shift, which is exactly when it is needed. Enrichment attached to the event is used; enrichment that requires a context switch is not.
Frequently asked questions
What is AI-driven Cyber Threat Intelligence?
AI-driven Cyber Threat Intelligence (CTI) uses AI to ingest, deduplicate, enrich, and operationalise threat feeds, turning raw indicators into context-aware decisions across the AI SOC.
How does Spharaka use IOC enrichment?
Spharaka enriches every IOC with reputation, geo, ASN, malware family, vulnerability links, and adversary attribution, then correlates against live and historical telemetry.
Does Spharaka support custom or sector-specific threat feeds?
Yes. Spharaka integrates commercial, open-source, ISAC, government, and customer-specific threat feeds in a unified CTI fabric.
Explore related capabilities
AI SOC Platform
Unified autonomous Security Operations Center.
Autonomous Threat Hunting
Continuous AI-driven threat hunting.
AI SIEM
AI log analytics and correlation.
AI SOAR
Autonomous response orchestration.
AI UEBA
User and entity behaviour analytics.
SAGE™ AI Model
Spharaka's proprietary Cybersecurity SLM that powers this capability.
Related use cases and guides
Five feeds converging into one deduplicated record, which then radiates enrichment onto the events it bears on, including one nineteen days old.
Intelligence-led detection of ransomware operators.
Evaluating Autonomous Defence
Where intelligence fits in an autonomous stack.
Capabilities
All eight capabilities, and where CTI sits among them.
See Spharaka Cyber Threat Intelligence in action
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