Anyone else here using Codeium's security scanner on their codebase and getting a bit overwhelmed by the noise? I love the idea of automated vulnerability detection, but the initial batch of results can feel like finding a needle in a haystack... if the haystack is also on fire 🔥. After tweaking our setup for a few weeks, I've found some solid strategies to cut down the false positives and make the signal much clearer.
The key is giving Codeium more context. It's not a magic bullet, but these steps made it *actionable* for our team:
* **Leverage the `.codeium/ignore` file.** This is your best friend. You can suppress specific rules, paths, or even entire vulnerability classes (like "hardcoded-secret" for a directory full of test fixtures). The format is straightforward:
```yaml
# .codeium/ignore
- vulnerability_id: "python/hardcoded-secret"
path: "tests/**"
- vulnerability_id: "js/use-of-insecure-random"
reason: "Legacy code, scheduled for refactor Q3"
```
* **Adjust severity thresholds in your project config.** If you're drowning in "low" and "info" level alerts that aren't relevant to your context, you can raise the bar for what gets flagged.
```yaml
# .codeium/config.yaml
security:
min_severity: "medium" # ignores low & info
```
* **Provide more precise file type detection.** Sometimes scanners misidentify file types. Explicitly marking non-production config files (e.g., `docker-compose.override.yml`) can help.
The biggest win for us was combining the ignore file with a focused, incremental rollout. Start by scanning only your `src/` or `app/` directories, not the entire repo with vendored dependencies and build artifacts. This drastically cuts the initial noise and lets you build a robust ignore list for your actual code.
Has anyone found other effective filters or integration tips? I'm particularly curious if there's a way to feed it a list of known-safe dependencies to skip library checks.
--diver
Data is the new oil - but it's usually crude.
Nice start on the ignore file - that's the exact pattern we landed on. A big caveat we found is you need to be *really* specific with those wildcards. Our first pass of `path: "configs/*"` accidentally suppressed a live production config file buried in that folder. We ended up defining each subdirectory explicitly.
The severity threshold tip is golden. We pushed ours to "medium" and above and instantly cut the alert volume by 70%. It let the team actually start *using* the scanner instead of just ignoring it. Do you find any genuinely important "low" severity findings slip through after doing that? We caught one in a legacy auth module, but that was about it.
Keep deploying!
The severity threshold is a pragmatic first filter, but calling it 'golden' is a bit much. It's a blunt instrument. You're trading noise for blind spots.
On the wildcards, your caution is dead right. I've seen teams get burned by that exact over-broad pattern. The real failure mode isn't just missing a production config - it's creating a hidden compliance gap. An auditor sees your shiny security scanner report, but has no idea that entire directories have been silently excused because someone was lazy with a glob pattern. You have to treat those ignore entries with the same rigor as a firewall rule.
To your question about low-severity findings: yes, they slip through constantly, but not in the way you think. The problem isn't the one-off legacy auth module. It's the aggregate risk. Ten 'low' severity issues in a single microservice? That's a medium or high-risk service profile. By filtering to 'medium and above,' you're telling your team to ignore architectural drift and concentration risk. You're optimizing for inbox zero, not system security.
Test the migration.
That ignore file format looks super clean - we started with a similar setup. One thing that tripped us up was forgetting to commit the `.codeium/` directory at first, so every dev's local setup was ignoring different things.
Raising the severity threshold is a great first filter, but we also got good mileage from tuning the scanner's confidence levels. Lowering it from "high" to "medium" for certain rules, like dependency checks, cut a ton of speculative alerts without losing real issues. It's a bit more granular than just adjusting severity.
Did you also find that some false positives were actually mis-categorized vulnerabilities? We kept getting "hardcoded-secret" flags on our public API keys in frontend configs, which are meant to be public. Had to add a bunch of path-specific overrides for that.
Cheers, Henry
If your main strategy is leaning on the ignore file, you've already lost. You're not tuning a scanner; you're manually building a whitelist of your own code to placate a noisy tool.
That's not reducing false positives. It's defining them, one by one, and hoping your list stays correct as the codebase changes. The moment you commit that ignore entry for "legacy code", you've just institutionalized a vulnerability.
Prove it
That whole post is optimizing for the wrong thing. You're not making the tool better. You're changing your code and habits to appease a badly tuned linter.
The real fix is pressuring the vendor. Why are we accepting a scanner that floods us with "hardcoded-secret" alerts for *public* API keys? That's a fundamental misunderstanding of context that you shouldn't have to teach it via ignore files.
Tweaking thresholds just means you're paying them to filter their own noise.
Agreed, it's all about context. That ignore file's format is simple, but it's a commitment. You have to treat it like a security policy - review it weekly, document every exception, and sunset entries with dates. If you don't, it becomes a junk drawer where vulnerabilities go to hide.
Raising the severity threshold is a good first filter, but it's a temporary fix. You still need to run a full scan, including lows, before major releases. Otherwise you're just shifting your compliance risk, not eliminating it.
Treating an ignore file like a weekly-reviewed security policy is the kind of well-intentioned governance that doubles your compliance overhead for no measurable gain. You're creating a second, manually-curated audit trail that will inevitably fall out of sync with the code.
The pre-release full scan idea is the real trap. It creates a perverse incentive to keep the severity filter high during development, ensuring a massive, unmanageable backlog of "low" issues to triage right before a deadline. That's when real vulnerabilities get waived through.
The cost of that process, in engineer hours spent reviewing junk alerts, probably exceeds the risk of the vulnerabilities you're catching.
pay for what you use, not what you reserve