惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

小众软件
小众软件
V
Visual Studio Blog
博客园 - 三生石上(FineUI控件)
Last Week in AI
Last Week in AI
Blog — PlanetScale
Blog — PlanetScale
爱范儿
爱范儿
J
Java Code Geeks
A
About on SuperTechFans
F
Fortinet All Blogs
B
Blog
aimingoo的专栏
aimingoo的专栏
H
Hackread – Cybersecurity News, Data Breaches, AI and More
Engineering at Meta
Engineering at Meta
Y
Y Combinator Blog
有赞技术团队
有赞技术团队
G
Google Developers Blog
Apple Machine Learning Research
Apple Machine Learning Research
V
V2EX
博客园_首页
博客园 - 叶小钗
罗磊的独立博客
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
D
Docker
云风的 BLOG
云风的 BLOG

ThreatDown by Malwarebytes

This SonicWall bug is 2 years old. Akira ransomware is still exploiting it. | ThreatDown AI threat so great that security “takes precedence over everything except critical business operations”  | ThreatDown How Grok unknowingly powers cybercrime | ThreatDown 74% of organizations exposed to shadow AI | ThreatDown The guardrails problem just played out on both sides of the same incident | ThreatDown The AI era of cybercrime has arrived: The 2026 Cybercrime in the age of AI report | ThreatDown Prinz Eugen ransomware: a deep dive into a new Go-based encryptor - ThreatDown by Malwarebytes GachiLoader adopts AI skill lure - ThreatDown by Malwarebytes The Attacks Hiding in Your Identity Logs - ThreatDown by Malwarebytes Weaponizing autonomy: The rise of malicious AI agent skills Why identity-based threats are the new battleground for cybersecurity CastleRAT attack first to abuse Deno JavaScript runtime to evade enterprise security 100% malware detection at 1.7% CPU: how ThreatDown stops Mac info stealers Machine-scale cybercrime: The 2026 State of Malware report How to prevent a rootkit attack The anatomy of an Akira ransomware attack AI-orchestrated cyberattacks Tracking remote ransomware attacks at their source Inside EDR-Freeze: How ThreatDown stops the attack before it spreads
The identity nobody is watching - ThreatDown by Malwarebytes
Rumna Mishra · 2026-04-15 · via ThreatDown by Malwarebytes

Your next serious breach will likely start with an identity that nobody was watching.

The next serious breach at your organization will probably start with an identity that nobody was watching. One with legitimate credentials, legitimate access, and behavior that appeared normal right up until it didn’t. 

It might be an employee. It might be an automated process. The type of identity matters less than the fact that nobody was watching it.

Identity is the last unmonitored layer 

Every security domain has a detection layer built for it. Endpoints have EDR. Networks have dedicated monitoring. But identity, the layer that governs who accesses what, when, and from where, has historically been treated as a prevention problem, not a detection one. 

Deploy MFA. Configure conditional access. Enforce password policies.

These technologies reduce the probability of compromise but they don’t tell you what happens after authentication. They don’t tell you whether a legitimate credential is being misused or whether behavior has shifted in ways that signal an active threat. 

Strong locks on the doors. Limited visibility once someone is inside. That gap exists for every identity in your environment, both human and non-human. 

The credentials nobody rotates 

Non-human identities make the problem acute: Service accounts with no MFA and passwords that go unchanged for years; Entra ID service principals carrying broad Microsoft Graph permissions; hardcoded secrets in scripts that are committed to repositories and forgotten; Okta API tokens created by administrators who have since left that are still valid, still powerful, and completely unmonitored. 

These credentials surface in dark web breach data too. Unlike a compromised human password, nothing forces a reset. The exposure persists. 

Posture management identifies the misconfiguration. It doesn’t catch the attacker already using it. 

What ITDR changes 

ITDR (Identity Threat Detection and Response) closes the gap that prevention controls leave open across every identity, human and non-human. 

For human identities: Continuous monitoring across Entra ID and Okta for impossible travel, suspicious access patterns, sudden privilege escalation, and credentials exposed on the dark web. 

For non-human identities: Behavioral baselines for service accounts and service principals, with real-time detection when they deviate, such as an API called for the first time, authentication from an unexpected location, a client secret used outside its normal context. 

The signals already exist in your identity platform logs. ITDR is the layer that watches them continuously and connects the dots before the damage is done. 

Why AI is the mechanism, not the marketing 

The scale of the problem is what makes AI necessary, not as a selling point, but as a practical requirement. 

No analyst watches millions of authentication events per day across every service account, every Entra ID sign-in, every Okta session. AI builds a behavioral baseline for each identity individually, what it accesses, when, from where, and in what sequence and detects when that baseline breaks, in real time, before the signal is buried in log volume. 

That matters because identity-based attacks are engineered to look normal. A threat actor operating through a compromised service principal doesn’t trigger a signature match. They authenticate the way the account always has. The deviation is behavioral: A subtle shift in timing, scope, or access pattern that no rule-based system would catch after the fact, but a trained model recognizes as it happens. 

This is what separates ITDR from a SIEM with identity-adjacent queries. The detection is continuous, per-identity, and adaptive. It closes the gap not by writing better rules, but by learning what normal looks like for each identity in your environment and alerting when something unexpected happens. 

The organizations getting ahead of this aren’t waiting for the breach that traces back to a forgotten service principal or a compromised employee account that went unnoticed for weeks. They’re treating identity as a security domain that requires detection and response and not just prevention. 

Every other layer in your stack has that. Identity is overdue.