Embedded software powers the world's most critical systems — automotive braking controllers, aircraft flight computers, medical infusion pumps, industrial PLCs. Yet security testing in embedded development has historically lagged years behind enterprise software. A single exploitable vulnerability in a connected vehicle or medical device can cause consequences that go far beyond data breaches — they can cost lives.
This is where Static Application Security Testing (SAST), and specifically Klocwork, becomes not just useful but non-negotiable.
Why Embedded Systems Present a Unique Security Challenge
Embedded software operates under severe constraints: limited memory, real-time execution, bare-metal C/C++, hardware-software co-design. Standard SAST tools built for Java or Python simply don't understand MISRA C, can't reason about hardware register access patterns, and generate overwhelming false positives on embedded code. Security teams abandon them — and embedded firmware ships with zero meaningful static analysis.
Industry data: 67% of embedded development teams conduct no formal security testing before release. Of those that do, fewer than 20% use automated static analysis. The attack surface is enormous and largely unguarded.
What Klocwork Does Differently
Klocwork performs deep semantic analysis of C, C++, Java, and Python — understanding how code executes, not just how it's written. It ships with built-in checkers for MISRA C 2012, MISRA C++ 2008, AUTOSAR C++14, CERT C/C++, CWE Top 25, and IEC 62443 — the standards that matter in embedded, automotive, and industrial development.
Incremental Scanning for Complex Build Systems
Embedded teams work with CMake, Make, IAR, and Keil. Klocwork integrates natively with these environments and supports incremental scanning — analysing only changed code. A build that takes hours to compile can be scanned for security issues in minutes, making it practical to run on every commit without slowing developers down.
Finding Vulnerabilities That Kill People
Buffer overflows, null pointer dereferences, use-after-free, integer overflows, race conditions — these aren't theoretical in embedded systems. They are the root cause of Toyota's unintended acceleration recall (buffer overflow in throttle control software), Therac-25 radiation therapy overdoses (race condition in control code), and dozens of automotive OTA remote code execution vulnerabilities.
// File: src/can_parser.c | Line: 247 | Severity: CRITICAL
void parse_can_frame(uint8_t *data, int len) {
char buf[64];
memcpy(buf, data, len); // ← KW: len can exceed 64 → OVERFLOW
}
// Suggested fix: if (len > (int)sizeof(buf)) return ERROR_OVERFLOW;
Compliance: ISO 26262, DO-178C, IEC 62443
Safety standards for embedded software mandate static analysis. DO-178C requires structural coverage analysis. ISO 26262 requires software unit design verification. IEC 62443 requires secure coding practices verification. Klocwork generates qualification evidence that directly feeds into these certification processes — for teams working towards ASIL-D or DAL-A, the hours saved in compliance evidence alone justify the investment.
CI/CD Integration for Embedded Teams
- Jenkins: Native Klocwork plugin triggers analysis on every firmware commit
- GitLab CI: Findings post as merge request comments — devs see issues before code merges
- Jira: Critical findings auto-create tickets assigned to the responsible developer
- IDE plugins: Eclipse, Visual Studio, IAR Embedded Workbench — real-time feedback as developers type
🔒 Try Klocwork Free for 14 Days
Full-featured access for your embedded C/C++ codebase. Our security engineers will set up, configure, and walk through your first scan results with you.
Start My Free 14-Day Trial →What Teams Typically Find in Their First Scan
Based on onboarding embedded teams onto Klocwork, a typical 500K-line automotive ADAS codebase reveals 15–40 critical/high findings (buffer overflows, null dereferences, memory leaks), 200–800 medium findings (uninitialised variables, dead code), and 50–150 MISRA C violations per 100K lines in legacy code. Over 85% of reported findings are genuine — not noise.
The question isn't whether your embedded software has vulnerabilities. Every complex codebase does. The question is whether you find them first — or an attacker does.