Socket is a great product. $65M in funding, customers like Anthropic and Vercel, a team of about 100 doing real work in supply chain security. They've earned their spot.
I built Dependency Guardian. I'm biased, so I'll tell you where Socket wins too. But the gap between these tools isn't what most people expect.
Dependency Guardian vs Socket.dev at a glance
| Dependency Guardian | Socket.dev | |
|---|---|---|
| Detection approach | 53 behavioral detectors (32 npm + 21 PyPI) + 78-rule cross-detector correlator | Static code inspection, ~70 risk signals |
| Published catch rate | 95.20% npm, 93.88% PyPI on 13,907-sample disclosed-malware corpus | Not published |
| Published false positive rate | 0.44% on 1,967 clean npm packages, 0.29% on 2,000 clean PyPI packages | Not published |
| Explainability | Named detectors, code patterns, line numbers | Risk category only |
| Evasion handling | 3-stage preprocessing: decodes hex/unicode/octal, strips invisible chars and comments before scanning | Standard static analysis |
| Runtime sandbox | gVisor with honeypot credential files (planned async deep-scan tier) | None |
| Ecosystems | npm, PyPI | 14+ (JS, Python, Go, Java, Ruby, Rust, and more) |
| Enterprise features (SSO, SBOM, VS Code ext) | Roadmap | Shipping |
| Pricing (100 devs/yr) | $12,000 (Team, $10/user/mo) | $30,000–$60,000 (Team $25, Business $50) |
| Free tier | Full detection, 1,000 scans/mo | Full detection, 1,000 scans/mo |
Behavioral npm scanning: explainable detectors vs opaque risk categories
Both tools exist because CVE-based scanners are blind to supply chain attacks. npm audit, Snyk, Dependabot — they check advisory databases. A brand-new malicious package doesn't have an advisory. By the time one exists, the damage is done. Socket and DG both analyze what packages actually do instead of looking them up in a list.
The difference shows up when something gets flagged.
Socket gives you a risk category: "install scripts," "network access," "obfuscated code." What you don't get is the logic behind the score. When your teammate looks at a flagged PR and asks "is this real?" you're on your own. You end up reading the package source yourself — which is the thing the tool was supposed to save you from.
DG shows named detectors, the code patterns that triggered them, and line numbers. The network exfiltration detector, the behavior drift detector, the child process detector. They aren't anonymous signals. You can trace a flag back to the exact line of code and decide in seconds whether it's legitimate.
Cross-detector correlation, not manual triage
There's another layer Socket doesn't have.
An install script is common. A network call is common. Obfuscation is suspicious. Any one of these in isolation is a shrug. All three in the same package is a confirmed attack pattern.
DG's correlator runs cross-detector rules across findings. When a package trips install_script + a credential read, or pairs obfuscation with credential theft, it doesn't just accumulate points — it fires a critical correlation rule, the score is pinned, and the PR is stopped automatically. Zero human triage.
Socket combines its signals into a single risk score. That score still lands on a human desk.
Evasion handling: the 3-stage preprocessing Socket doesn't run
Attackers know scanners pattern-match. So they stop pattern-matching: they hide payloads in zero-width spaces, backtick template strings, hex-encoded literals, Unicode-escaped identifiers, comment-embedded code.
Before any DG detector runs, the code goes through three preprocessing passes:
- Strip comments (including comment-embedded payload blocks)
- Strip invisible Unicode (ZWSP, RTL marks, BOMs)
- Decode all string escapes — hex, unicode-4, unicode-curly, octal — in that order
Detectors then see the decoded source. If an attacker wrote \x65\x76\x61\x6c, the detector sees eval.
Socket does standard static analysis on the raw source. Public Socket documentation doesn't describe a comparable normalization pass.
Receipts: published TPR/FPR vs marketing claims
Socket claims "over 100 zero-day attacks detected every week." I believe them. But they don't publish a catch rate, a false positive rate, or a validation methodology. There's no denominator. If you're sitting in front of your CISO justifying a tool purchase, "they say they catch a lot" doesn't close the conversation.
DG publishes the numbers:
- npm: 95.20% catch rate (8,903 of 9,352 disclosed-malware packages)
- PyPI: 93.88% catch rate (4,276 of 4,555 disclosed-malware packages)
- False positive rate: 0.44% on 1,967 clean npm packages, 0.29% on 2,000 clean PyPI packages
- Validation set: 17,874 packages; methodology published at /benchmark
I'm not claiming these beat Socket's real-world performance. Maybe they catch more. Maybe less. I don't know, because the data isn't public. What I do know: "94.77% combined catch rate on a 17,874 malware corpus with published methodology" lands differently in a budget meeting than a claim that asks for faith.
Reachability ≠ malware detection: why Socket's Coana acquisition doesn't close the gap
Socket recently acquired Coana for reachability analysis. Reachability tells you whether a known CVE in a dependency is actually called by your code. That's a useful noise-reduction tool for vulnerability triage.
It doesn't help with supply chain attacks.
Malware executes on npm install via install scripts, or on import, or on a timer after deployment. It doesn't care whether your code "reaches" it — it doesn't need to. A reachability analyzer looking at a compromised version of axios sees the normal request-sending function path and the RAT beacon sitting quietly in a postinstall hook, and correctly reports the RAT as "reachable because postinstall runs." The insight you actually need — this is malware — comes from behavioral analysis, not reachability.
DG is built for the malware problem. Socket is bolting CVE triage onto a malware scanner.
Structural anomaly detection: catching novel attacks before anyone writes a rule
Every rule-based scanner has the same limitation: it can only catch what someone wrote a rule for. The first instance of any new attack pattern is invisible until a human sees it, classifies it, and writes the rule.
DG's structural-anomaly detector compares each package's shape against the known-clean corpus — file count distributions, dependency graph shape, manifest-vs-code coherence, tarball-vs-registry mismatches. Packages that are structurally weird get flagged for deeper review even when they don't match any specific pattern. Combined with the metadata detectors (phantom dependencies, fresh-publish windows, maintainer-change signals), novel attacks still trip enough signals to land on the correlator's radar.
Feed monitoring: threats caught before developers install them
DG runs a pre-scanner that watches the npm and PyPI publish feeds continuously. Packages get scored the moment they're published. By the time a developer runs npm install on something brand-new, DG already knows whether it's suspicious.
Socket scans on request. That's fine for triage, but it means the first developer to install a malicious zero-day package is the canary.
Where Socket wins
Ecosystem breadth. Socket supports 14+ language ecosystems. DG covers npm and PyPI. If your stack includes Go, Java, Ruby, or Rust, Socket covers those and we don't. For some teams, that ends the conversation before it starts.
Enterprise features today. Socket ships SSO, SBOM export, Vanta integration, and a VS Code extension. DG has these on the roadmap but doesn't offer them yet. If those are hard requirements this quarter, Socket is the right call this quarter.
Mindshare and integration inertia. Socket is the default recommendation in a lot of security-tooling threads. That's real — it means more third-party integrations, more battle-tested deployments, more examples to copy.
Pricing: $12K vs $60K at 100 developers
Socket's pricing tiers:
- Team: $25/dev/month
- Business: $50/dev/month
- Enterprise: custom
DG's pricing:
- Free: $0, 1,000 scans/mo, full detection
- Pro: $15/month flat (not per-seat), 5,000 scans, up to 5 seats
- Team: $10/user/month, unlimited scans
- Enterprise: custom
A 100-developer org on Socket Team pays $30K/year. On Socket Business, $60K/year. On DG Team, $12K/year. Same detection depth on every plan — the free tier has the same 35 detectors and correlator as Enterprise. Volume scales, capability doesn't.
If you're a small team, DG Pro at $15/month flat covers your whole org for less than Socket charges for one developer.
See for yourself
Pick a package you already depend on and run it through the public scanner. Read the detector output. That'll tell you more about whether DG's transparency matters to your team than anything I write here.
Scan a package · Benchmark methodology · Pricing
FAQ
Is Dependency Guardian cheaper than Socket.dev?
Yes. DG Team is $10/user/month vs Socket Team at $25 and Socket Business at $50. At 100 developers, DG costs $12,000/year; Socket Team is $30,000 and Socket Business is $60,000. Both tools include full detection on the free tier.
Does Socket.dev publish its catch rate?
No. Socket publishes a weekly count of zero-days detected but does not publish a true-positive rate, a false-positive rate, or a validation methodology. DG publishes all three at /benchmark: 95.20% npm catch rate, 93.88% PyPI catch rate, 0.44% npm FPR + 0.29% PyPI FPR on the 17,874-package OSSF MAL + Datadog corpus.
Which tool supports Go, Java, Ruby, or Rust?
Socket. DG currently covers npm and PyPI only. Other ecosystems are on the roadmap but not shipping. If you need multi-ecosystem coverage today, Socket is the right choice.
Can Dependency Guardian catch obfuscated or Unicode-escaped malware?
Yes. DG runs a 3-stage preprocessing pipeline before any detector executes: strips comments, strips invisible Unicode characters, and decodes all string escapes (hex, unicode-4, unicode-curly, octal). Detectors see the normalized source, so \x65\x76\x61\x6c is scanned as eval.
Does Dependency Guardian use runtime sandboxing like Socket?
Socket doesn't sandbox. DG has a gVisor-based behavioral sandbox on dedicated hardware that runs packages in isolated containers with honeypot credential files planted inside — if a package touches them, it's an automatic block. The sandbox is currently paused and planned to re-enable as an async deep-scan tier.
How do Socket's risk categories compare to DG's detectors?
Socket reports a risk category (e.g. "install scripts," "network access"). DG reports a named detector, the code pattern that triggered it, and the line number. Both surface the same underlying signals; the difference is whether an engineer reviewing a flagged PR has enough information to decide in seconds or has to go read the package source themselves.
Is Socket's Coana acquisition relevant to supply chain attack detection?
No. Coana does reachability analysis for CVEs — useful for triaging known vulnerabilities, not for catching malicious packages. Malware runs on install or import regardless of whether your code "reaches" it. Reachability and malware detection solve different problems.