Python
JavaScript
Java
C++
Rust
Ruby
PHP
Elixir
Signalis.watch
Recorded Future
Feedly
ThreatConnect
CrowdStrike Falcon
Cyberpion/Threat Intelligence Platforms
Emerging Threats Intelligence
Inoreader
Signalis monitors curated CTI sources and extracts structured fields from every report. You read one ranked feed instead of many source sites.
Public threat reporting is scattered across vendor blogs, CERT advisories, and researcher posts, each with its own naming conventions and no consistent structure. Signalis ingests these sources continuously and processes every report through an extraction pipeline that identifies:
On top of the structured corpus: watchlist alerts for the actors and sectors you track, weekly email digests, grounded Q&A with enforced citations to source reports, and a machine-readable IOC feed API with OpenAPI spec.
Sources are continuously scored on extraction yield. Feeds that stop producing signal get cut, so the feed stays high-density.
Built by a former enterprise CTI practitioner (OpenCTI, MISP, EclecticIQ background) as the middle path between manually reading source sites and five-figure enterprise threat intel platforms.
Pricing: Free tier with the full pipeline on 7-day-delayed data. Real-time feed, alerts, and API from $29/mo. Teams with 5 seats, webhooks, and higher API limits at $69/mo.
Python Signalis.watchNo Signalis.watch videos yet. You could help us improve this page by suggesting one.
Signalis.watch's answer:
Signalis turns dozens of scattered CTI sources into one structured, ranked feed. Instead of skimming vendor blogs, CERT advisories, and researcher posts separately, you read a single stream where every report has been processed into structured fields: threat actors (canonicalized across vendor naming schemes), CVEs, IOCs, targeted sectors, and severity. IOCs are extracted with defang handling and are careful about what counts as an indicator, reference links are kept as references, not polluted into the IOC set. The result is a feed you can query like data, not a pile of articles: via the dashboard, watchlist alerts, weekly digests, or a machine-readable IOC API.
Signalis.watch's answer:
Most aggregators stop at collecting links. Signalis is built by a former enterprise CTI practitioner (OpenCTI/MISP/EclecticIQ background) and it shows in the details: actor names are canonicalized so "one campaign" doesn't appear as five actors, extraction quality is continuously measured against source-level yield metrics, and low-signal sources get cut. It's also priced for individual analysts and small teams, real-time structured feed, alerts, and IOC API access from $29/mo, where traditional threat intel platforms start at five figures. Free tier lets you evaluate the full pipeline on 7-day-delayed data before paying anything.
Signalis.watch's answer:
CTI analysts, SOC analysts, threat hunters, and security engineers at organizations too small for enterprise TIP pricing, or individual practitioners who want to stay current without maintaining their own feed pipeline. Also useful for MSSPs and consultants who need structured, citable threat reporting across many client sectors.
Signalis.watch's answer:
Signalis was built by a threat intelligence practitioner who spent years running enterprise CTI platforms and doing the same manual triage every morning: dozens of source sites, inconsistent naming, unstructured reports. The tooling that solved this was enterprise-priced and heavier than most teams need. Signalis is the middle path: an opinionated ingestion and extraction pipeline that reads the sources for you and outputs structured intelligence: one feed, every report structured.
Signalis.watch's answer:
FastAPI (Python) backend with PostgreSQL, a Next.js/Tailwind frontend, Redis for rate limiting, and an LLM-assisted extraction pipeline layered over deterministic regex IOC extraction with defang/refang handling. Auth via Supabase, deployed on hardened Linux infrastructure.
Based on our record, Python seems to be more popular. It has been mentiond 299 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
137Foundry provides legacy modernization services that include dependency mapping as a foundational assessment phase. Prettier and ESLint are useful companion tools for enforcing code style consistency as the refactoring proceeds. Node.js and Python.org official documentation are authoritative references for understanding the import and module systems of those runtimes. - Source: dev.to / 2 months ago
For Python codebases, tools like Python's built-in ast module and import analysis scripts can generate call graphs. For JavaScript, ESLint and module analysis tools serve a similar purpose. GitHub advanced search can help you find all internal references to a specific function across a large repository. - Source: dev.to / 2 months ago
Import asyncio Import aiohttp From bs4 import BeautifulSoup Async def scrape_and_parse(url: str, session: aiohttp.ClientSession) -> dict: async with session.get(url) as response: html = await response.text() # BeautifulSoup parsing happens after the await โ no issue soup = BeautifulSoup(html, "html.parser") return { "url": url, "title": soup.title.string if soup.title... - Source: dev.to / 3 months ago
**_Beginner mistake to avoid_** - Writing SQL only inside DBeaver - Always save SQL files in VS Code and commit them **Using PostgreSQL with Python** _**What Python does here**_ Python talks to PostgreSQL and says: - โSave this dataโ - โGet this dataโ - PostgreSQL listens. Python works. _**Step 1: Install Python **_ - Download from https://python.org - During install, check Add Python to PATH Screenshot... - Source: dev.to / 6 months ago
Import time Import requests Import asyncio Import aiohttp Urls = [ 'https://example.com', 'https://httpbin.org/get', 'https://python.org' ] # Synchronous version Def sync_fetch(): for url in urls: response = requests.get(url) print(f"{url} fetched with {len(response.text)} characters") # Async version Async def async_fetch(): async with aiohttp.ClientSession() as session: ... - Source: dev.to / 9 months ago
JavaScript - Lightweight, interpreted, object-oriented language with first-class functions
Recorded Future - Recorded Future provides organizations with real-time threat intelligence.
Java - A concurrent, class-based, object-oriented, language specifically designed to have as few implementation dependencies as possible
Feedly - The content you need to accelerate your research, marketing, and sales.
C++ - Has imperative, object-oriented and generic programming features, while also providing the facilities for low level memory manipulation
ThreatConnect - ThreatConnectโs intelligence-driven security operations is the only solution with intelligence, automation, analytics, and workflows in one platform.
