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SQL Injection in user.js:142
User input flows directly to query. High confidence.
Missing null check in api.js:89
Input validated upstream in middleware. False positive.
Outdated lodash dependency
Vulnerable method not used. Lower priority.
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From vulnerability detection to automated fixes, Orbis AppSec handles security so you can focus on building features.
Deep Code Analysis
Static analysis that goes beyond pattern matching. Understands data flow, control flow, and business logic.
AI-Powered Context
Our AI understands your codebase like a senior engineer, reducing false positives and prioritizing real threats.
Auto-Fix Magic
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Dependency Scanning
Full SCA coverage for npm, pip, maven, and more. Know exactly which packages put you at risk.
GitHub Native
PR comments, status checks, and automated scans. Security that fits your existing workflow.
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Map findings to SOC 2, PCI DSS, HIPAA, and more. Generate audit-ready reports in one click.
How Orbis AppSec works
Get from zero to secure in four simple steps. No complex setup, no learning curve.
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Scan
Orbis AppSec analyzes your code for vulnerabilities, misconfigurations, and dependency risks.
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Fix
Apply AI-generated fixes directly or export to your issue tracker.
Not just another scanner. Your AI security teammate.
Traditional scanners blast you with alerts. Orbis AppSec thinks like a security engineer — understanding context, filtering noise, and delivering fixes you can actually use.
Contextual Understanding
Unlike pattern-matching tools, Orbis AppSec understands your code's intent and business logic.
90% Fewer False Positives
AI filters out noise so your team focuses on real vulnerabilities, not chasing ghosts.
Smart Prioritization
Findings ranked by actual exploitability, not just severity scores.
Instant Fix Generation
Production-ready code fixes generated in seconds, reviewed by AI for correctness.
Orbis AppSec AI Analysis
Processing findings...
SQL Injection in user.js:142
CriticalMissing null check in api.js:89
DismissedOutdated lodash dependency
MediumReal Vulnerabilities, Real Fixes
Learn from security vulnerabilities we've discovered and fixed in production code
Voice Assistant Command Injection via os.system() f-String
A critical command injection vulnerability in a voice assistant's audio playback handler allowed attackers to execute arbitrary shell commands by manipulating file paths passed to os.system(). The fix replaces shell invocation with subprocess calls and direct OS APIs, eliminating shell metacharacter interpretation entirely.
`requests.get()`/`delete()`/`post()` with `verify=False` in Release
A critical security vulnerability in a release automation script disabled SSL certificate verification on every HTTPS request to GitHub's API. By passing `verify=False` to `requests.get()`, `requests.delete()`, and `requests.post()`, the script exposed OAuth tokens and release binaries to man-in-the-middle attacks on any network the script ran from.
LDAP Filter Injection in da_unique_email_validator Fixed
The registration-time email uniqueness validator, `da_unique_email_validator`, formatted the submitted email address straight into an LDAP search filter with Python's `%` operator, so filter metacharacters in the email were interpreted as filter syntax. The fix wraps the value in `ldap.filter.escape_filter_chars()` (and imports the `ldap.filter` submodule explicitly), so a submitted address is always treated as a literal attribute value. Any deployment with `ldap login` enabled and a bind accoun
ExternalHttpClient::request() Sent Basic Auth Over Plain HTTP
The `ExternalHttpClient::request()` helper accepted a `$basicAuth` string and passed it straight to the HTTP client's `auth` option without checking that the target URL used `https://`. Any external JSON data source configured with an `http://` endpoint therefore shipped a base64-encoded `Authorization: Basic` header in cleartext on every scheduled load. The fix rejects the request outright — before a client is even created — when the URL scheme is not HTTPS.
SQL's Insert() and Update() Methods Used F-String Interpolation in u2share_batch_give_sugar
The SQL helper class in u2share_batch_give_sugar used Python f-strings to construct INSERT and UPDATE queries, creating SQL injection vulnerabilities even though values appeared to come from internal constants. The fix replaces all f-string query construction with sqlite3 parameterized queries using `?` placeholders, eliminating string interpolation entirely from the database path.
deleteNestedProperty Prototype Pollution via Dot-Notation Path
The `deleteNestedProperty` function in propertyUtils.ts allowed attackers to manipulate JavaScript object prototypes by passing specially crafted dot-notation paths like `__proto__.polluted`. A fix now blocks dangerous keys before processing, preventing prototype pollution attacks that could affect all objects in the application.
Compliance frameworks, covered
Map your security findings to industry standards. Generate audit-ready reports that satisfy your compliance team and auditors.
SOC 2
Type II Ready
PCI DSS
Level 1 Compliant
HIPAA
Healthcare Ready
OWASP
Top 10 Coverage
ISO 27001
Information Security
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Export findings mapped to specific compliance controls
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Automatic documentation for audit trails
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