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11/07/2026 8:42 pm
TL;DR: Threat intelligence has shifted from data collection to contextual decision support, with SecurityScorecard arguing that effective programmes now blend OSINT, dark web monitoring, internal telemetry, and machine-assisted analysis to predict likely attack vectors and guide defensive investment. That matters because identity, secrets, and third-party access are increasingly where intelligence turns into prevention.
NHIMG editorial — based on content published by SecurityScorecard: What is Threat Intelligence in Cybersecurity? A Comprehensive 2025 Overview
By the numbers:
- 80% of identity breaches involved compromised non-human identities such as service accounts and API keys.
- 97% of NHIs carry excessive privileges, increasing unauthorised access and broadening the attack surface.
- Only 5.7% of organisations have full visibility into their service accounts.
Questions worth separating out
Q: How should security teams use threat intelligence to protect service accounts and API keys?
A: Start by mapping intelligence sources to the identities most likely to be abused, especially service accounts, API keys, certificates, and third-party tokens.
Q: Why do NHIs make threat intelligence harder to operationalise?
A: NHIs multiply the number of access paths that can be exposed, abused, or inherited across automation and vendor relationships.
Q: What do security teams get wrong about threat intelligence programmes?
A: They often treat intelligence as a detection layer instead of a decision layer.
Practitioner guidance
- Tie threat feeds to identity assets Map indicators from commercial, open source, and internal intelligence directly to service accounts, API keys, certificates, and vendor accounts so analysts can see which identities are implicated.
- Build revocation triggers into the intelligence workflow Create predefined actions for exposed credentials, including rotation, token revocation, and session termination, so intelligence findings become control changes rather than ticket backlog.
- Add third-party access to intelligence scope Include supplier risk feeds, vendor compromise alerts, and partner exposure signals in the same workflow used for internal identity events, because third-party access often becomes the first abuse path.
What's in the full article
SecurityScorecard's full guide covers the operational detail this post intentionally leaves for the source:
- Step-by-step breakdown of the threat intelligence lifecycle from collection through feedback and review
- Source categories such as OSINT, dark web monitoring, honeypots, HUMINT, and internal telemetry
- Threat intelligence tool categories including TIPs, SIEM integration, and malware analysis platforms
- Practical examples of how to apply intelligence to vulnerability remediation and security investment decisions
👉 Read SecurityScorecard's 2025 guide to threat intelligence in cybersecurity →
Threat intelligence in 2025: what identity teams should change?
Explore further
11/07/2026 9:09 pm
Threat intelligence is becoming an identity control plane, not just a detection function. The guide emphasises contextual analysis, but the real shift is that intelligence now has to drive identity decisions around exposed secrets, third-party access, and privileged accounts. That makes threat intel part of governance, because the question is no longer only what happened but which identity path must be cut off next.
A question worth separating out:
Q: Who should own action when threat intelligence identifies exposed credentials?
A: Ownership should sit with the team that can execute the identity action, not just the team that discovered the signal. In most organisations that means IAM, PAM, cloud security, or the service owner, depending on the identity type. The governance model should specify who can revoke, rotate, or disable access before the issue becomes a breach.
👉 Read our full editorial: Threat intelligence in 2025 needs identity-aware context
