CWE-400
Runtime detection of processes that consume excessive CPU, memory, disk, or network bandwidth due to algorithmic complexity or missing input constraints....
Precogs AI Insight
"Precogs AI runtime analysis identifies resource exhaustion vectors through crafted inputs that trigger worst-case algorithmic complexity."
What is CWE-400 (Uncontrolled Resource Consumption)?
Runtime detection of processes that consume excessive CPU, memory, disk, or network bandwidth due to algorithmic complexity or missing input constraints.
Vulnerability Insights
In the context of binary ai-powered dast vulnerabilities, this vulnerability poses significant risk because compiled binaries and complex AI logic cannot be easily patched without vendor cooperation. Organizations relying on third-party software must use structural analysis tools to detect these flaws.
Impact on Systems
- Memory Corruption: Crashing the daemon process
- Execution Flow Hijacking: RCE via buffer overwrites
Real-World Attack Scenario
The attacker sends a carefully structured, oversized binary payload via the network interface. The vulnerable memory function processes the blob without checking size constraints, overwriting adjacent memory spaces or the instruction pointer. This allows the attacker to execute embedded shellcode or achieve a denial-of-service state.
Code Examples
Vulnerable Implementation
void process(char *input) {
char buf[256];
// VULNERABLE: Risky memory operations
sprintf(buf, "Data: %s", input);
}
Secure Alternative
void process(char *input) {
char buf[256];
// SECURE: Bounds-checked operations
snprintf(buf, sizeof(buf), "Data: %s", input);
}
Remediation
Ensure robust input validation, boundary checking, and adherence to secure architecture frameworks when designing Binary DAST solutions. Use automated code scanning or binary analysis to detect flaws early in the SDLC.