I've been evaluating Semgrep for a few months now across several client engagements, primarily for lightweight, incremental SAST in CI pipelines. The prevailing sentiment I've seen is that it's a "fast grep," but I think that undersells its utility for real-world SaaS application security.
My initial take is that Semgrep excels in its core promise: providing fast, targeted, and highly customizable security scanning without the heavy lifting of a full-blown SAST platform. It's particularly effective for:
* Enforcing consistent code patterns and internal best practices (e.g., "always use our safe wrapper for this API")
* Catching a well-defined subset of security issues (OWASP Top 10 basics, secret detection) with low false positives
* Integrating into fast-paced development cycles where a 30-minute scan is a non-starter
However, its depth can't match heavyweight SAST tools for complex data-flow analysis. You're not going to find the most subtle vulnerability chains with it.
I'm curious to hear from other teams who have adopted it, especially regarding:
* **Rule Management:** How have you structured custom rules? Do you maintain a central registry or per-project rulesets?
* **False Positive Triage:** What's your workflow for vetting findings? Does the speed make up for any lack of sophistication?
* **Pricing & Scaling:** For those on the Team/Enterprise tiers, how has the pricing model held up as you've scaled? Any surprises?
* **Migration Path:** If you moved from another SAST tool (like SonarQube, Checkmarx), what was the key driver and outcome?
Let's keep this grounded in specific use cases and evidence. This isn't about "best," but about understanding where Semgrep fits and where it might not.
You're not wrong about its role, but calling it "lightweight SAST" feels like we're grading on a curve. It's a linter with good marketing.
On rule management, the central registry approach is a trap if you're dealing with multiple client environments. You end up with a sprawling ruleset that tries to cover every tech stack, and suddenly you're back to managing a "full-blown platform," just a poorly documented one. Per-project rules decay into copy-paste chaos within six months.
I've seen teams get sold on the simplicity, then spend more time wrangling YAML and debating false positives than they ever did waiting for a traditional scan. It works until you need governance, then you're shopping for another tool to manage your "lightweight" tool.
Your mileage will vary
Your take on rule management is exactly where I've seen teams trip up. The central registry becomes a dumping ground for every junior dev's pet rule, and per-project rules become unmaintainable snowflakes.
What actually worked for us was to treat custom rules like any other infrastructure-as-code artifact, not a separate knowledge base. We store them in a dedicated Git repo, versioned alongside our pipeline definitions, with a strict CI process for contributions that requires a sample of violations and false positives. We only ever import that entire repo into projects, never individual rules.
It shifts the work from "managing YAML" to managing a small library of high-confidence patterns that you can actually document and test. You still won't catch subtle data-flow bugs, but you'll reliably block the stupid stuff everyone agrees on.