Cybret AI Blog
Research, analysis, and practical guidance on application security reachability.
What runtime correlation adds to static reachability analysis
Static graph traversal tells you which paths could be reached. Runtime signals tell you which ones are active right now. Combining both changes the triage question from possible-risk to current-risk.
Attack path analysis: a practical introduction for AppSec teams
Most AppSec teams have heard the term but few have a working definition. This post explains what attack path analysis actually means in the context of microservice applications and what it takes to compute it properly.
Why dependency graphs and static scans measure different things
A dependency graph answers what does this service use. A static scan answers where are the known-vulnerable patterns. Neither answers can an attacker get to the data. Here is what the third question requires.
The quiet cost of false-positive fatigue in security teams
Developers who dismiss scanner alerts as noise are not being negligent. They are responding rationally to a system that has trained them to expect irrelevance. Reachability context is the structural fix, not better alert wording.
Supply chain vulnerabilities and exposure path analysis: what changes
Third-party components introduce vulnerabilities you did not write. The reachability question is the same: does a path from an exposed entry point reach the vulnerable node in your specific deployed topology?
Shift-left is necessary but not sufficient for modern AppSec
Scanning at commit time catches known patterns early. It does not tell you how the running application composes those components into traversable paths. The shift-left layer and the graph-reasoning layer do different jobs.
How API surface growth changes your actual attack surface
Each new API endpoint is a potential entry point. The question is not how many endpoints you have but which of those endpoints can be traversed to reach sensitive data through your service graph. Surface area and reachable attack surface are not the same thing.
Secret exposure in microservice architectures: the graph problem
Secrets management tooling controls where secrets live. Exposure path analysis asks the harder question: given your service topology, how many paths from user-reachable entry points can reach a node that has access to a secret?
Where platform engineering and AppSec responsibilities actually overlap
Platform engineers own the runtime, the service mesh, and the secrets layer. AppSec teams own vulnerability triage. The overlap is larger than most org charts suggest, and it is exactly where exposure path analysis is most useful.
Third-party integration risk and the application graph
When you integrate a third-party service, you extend your service graph with a node whose internal behavior you cannot inspect. The reachability question becomes: what sensitive data can a compromised third-party integration access through your topology?
Zero-day response: why reachability is the first question to answer
When a critical CVE drops in a widely-used library, the first operational question is not do we use this? but does the vulnerable component sit on a path an attacker can reach from outside? Without graph context, that question takes days to answer manually.