Automated Triage
AI models can now analyze NVD feeds in real-time, categorizing severity not just by CVSS score, but by **exploitability context**. Large Language Models (LLMs) can parse unstructured vendor advisories to extract critical affected version ranges that structured feeds often miss.

Predictive Analysis
By training on historical exploit data, machine learning algorithms can predict which vulnerabilities are most likely to be weaponized in the wild, allowing defenders to prioritize patches before an attack occurs.

The Human Element
While AI acts as a force multiplier, the human analyst remains the final line of defense. The goal is not replacement, but augmentation—freeing up experts to focus on novel threats while AI handles the noise.

The Power of Programmable Surveillance

Our API allows you to query the extensive CVE database programmatically. Instead of searching the web, your scripts can ask specific questions: "Show me all critical vulnerabilities affecting Apache Log4j released in the last 24 hours."

Example: Python Alerting Script

import requests

def check_new_cves(vendor, product):
    url = "https://api.brilliantdog.io/v1/cves"
    params = {
        "vendor": vendor,
        "product": product,
        "min_cvss": 9.0,
        "published_since": "24h"
    }
    response = requests.get(url, params=params)
    return response.json()

# Check for critical Chrome issues
alerts = check_new_cves("google", "chrome")
if alerts:
    send_slack_notification(alerts)

Integrating with SIEM/SOAR

This data doesn't just have to live in scripts. You can pipe the API output directly into Splunk, Elastic, or XSOAR. This enriches your existing dashboards with real-time vulnerability context, allowing analysts to correlation active threats with known vulnerabilities.

Getting Started

Check out our API Documentation to generate your entry token. The free tier supports up to 1000 requests per day—more than enough to protect most small to medium environments.

1. The "If It Ain't Broke" Bias

Developers are incentivized to ship features and maintain uptime. A patch offers zero visible value to the customer but carries a non-zero risk of breaking the application. This risk-reward asymmetry makes inaction feel safer than action.

2. Alert Fatigue

When everything is "Critical," nothing is. Vulnerability scanners often flood teams with hundreds of alerts, many of which are false positives or technically unreachable. This leads to desensitization, where genuine threats get lost in the noise.

3. The fear of "The Big Rewrite"

Sometimes a security patch requires a major version upgrade of a framework or language (e.g., Python 2 to 3, or AngularJS to Angular). This isn't a patch; it's a project. Without allocated time, these debts accumulate until they become unmanageable.

Overcoming Patch Paralysis

• Automated Testing: The only cure for the fear of breaking things is a robust test suite. If you trust your tests, you can trust automated patching.
• Patch Budgets: dedicate 10-20% of every sprint to maintenance and security debt.
• Blameless Culture: If a patch breaks production, fix it and learn. If teams are punished for downtime caused by patching, they will stop patching.

1. Asset Discovery and Classification

You can't protect what you don't know about. The foundation of any VM program is a comprehensive, up-to-date asset inventory. This includes not just servers and workstations, but cloud resources, containers, and IoT devices. Classify these assets based on their criticality to the business to prioritize remediation efforts.

2. Continuous Scanning

Weekly or monthly scans leave massive blind spots. Implement continuous scanning capabilities that automatically assess new assets as they spin up. Integrate scanning into your CI/CD pipelines to catch vulnerabilities before they reach production.

3. Risk-Based Prioritization

Not all CVSS 9.8 vulnerabilities are created equal. A "critical" vulnerability on a text-gapped backup server is less urgent than a "high" vulnerability on your external web gateway. Use threat intelligence to contextulize vulnerabilities—prioritize those with known exploits (KEV) or those affecting high-value assets.

4. Automated Remediation & Mitigation

Where possible, automate the patching process. For vulnerabilities that can't be immediately patched, implement compensating controls (like WAF rules or network segmentation) and document them as temporary mitigations.

5. Metrics and Continuous Improvement

Track metrics that matter. "Mean Time to Remediate" (MTTR) is a classic, but also track "Risk Reduction Over Time" and "Coverage Percentage". specific goals (e.g., "remediate criticals within 48 hours") and hold teams accountable.

Building a mature program takes time, but the shift from "scanning" to "managing risk" is the most impactful change a security team can make.

The "Iceberg" of Modern Code

When you write an application today, you might write 10% of the code. The other 90% comes from libraries, frameworks, and modules downloaded from npm, PyPI, or Maven. You are essentially assembling parts manufactured by strangers.

Types of Supply Chain Attacks

• Typosquatting: Attackers publish packages with names similar to popular ones (e.g., reqeusts instead of requests), hoping developers make a typo.
• Dependency Confusion: Tricking build systems into pulling a malicious public package instead of a private internal one.
• Compromised Maintainers: Attackers use social engineering or credential theft to gain control of a legitimate package and inject malicious code.

Securing the Chain

1. SBOM (Software Bill of Materials): Generate an SBOM for every build. You need a complete list of ingredients to know if you're affected by a recall.
2. Lock Files: Always use lock files (package-lock.json, yarn.lock) to ensure consistent builds.
3. Vulnerability Scanning: Scan your dependencies at every stage—development, build, and runtime. Usage of tools like npm audit is a bare minimum.

Your application is only as secure as its weakest dependency. It's time to treat open source code with the same scrutiny as your own.