Cybersecurity Made Simple
FortySecurity helps companies keep their websites, apps, cloud, and devices safe—explained in plain language, backed by deep technical expertise.
From websites to mobile apps, cloud to connected devices—we test it the way a real attacker would, then explain the risks in language your whole team can act on.
Our security research has resulted in multiple CVEs and acknowledgments in Apple's Security Hall of Fame. We maintain active participation in bug bounty programs and vendor vulnerability research programs.
Our lead researcher xploiterr maintains a top ranking on HackerOne. View HackerOne profile →
We approach security testing from an attacker's perspective. Our assessments are informed by active security research, vulnerability discovery, and real-world exploitation techniques.
We think like attackers. Our testing methodology focuses on realistic attack scenarios, not compliance checklists.
Our testing techniques are validated through active security research and vulnerability discovery.
We go beyond surface-level testing. Firmware analysis, protocol reverse engineering, and custom exploit development when needed.
Every finding includes remediation guidance, risk context, and prioritized recommendations for immediate implementation.
Short, plain-English breakdowns of real attacks, recent incidents, and the small fixes that prevent big problems.
A wave of malicious npm packages hit thousands of projects this year. Here is what happened in plain English, why it kept spreading, and the five quick checks every team should run this week.
Hardcoded keys, weak SSL pinning, screenshots leaking secrets—here are the recurring issues we still find on iOS and Android, with one-line fixes for each.
Public S3 buckets and over-permissive IAM roles still cause most cloud breaches we investigate. A short tour of the patterns we keep finding—and how to spot them in 10 minutes.
Untrusted documents can hijack model behavior. We outline trust boundaries, safe retrieval patterns, and guardrails that actually work in production.
A clear checklist for bounding tool permissions, validating tool outputs, and preventing multi-step action chaining.
Prevent sensitive prompts, tokens, and embeddings from escaping into logs, traces, or third-party tools used by AI teams.
In the past year a series of malicious npm packages spread through stolen maintainer tokens, lookalike package names, and worm-like post-install scripts. Thousands of unrelated projects pulled the bad code without anyone touching a keyboard. Here is what we learned helping clients clean up—and the simple habits that would have prevented most of it.
Attackers used three repeating tricks. First, they phished or stole publish tokens from maintainers of popular packages, then pushed a new version that ran a small post-install script. Second, they registered packages with names that looked like real ones (one letter off, or a different casing) and waited for tired developers to typo. Third, some payloads were worm-like: once installed on a developer's machine, they searched for other npm tokens and re-published malicious updates from those accounts too.
The result was a chain reaction. A single compromised maintainer could indirectly ship code into projects that never imported their package at all.
npm install.^1.2.3 mean tonight's build can pick up code that did not exist yesterday.package-lock.json or pnpm-lock.yaml is committed, reviewed in PRs, and used by CI with npm ci or equivalent. No floating versions for releases.npm install --ignore-scripts in CI is safe and stops the most common payload path. Whitelist the few packages that genuinely need post-install builds.npm install runs.npm audit --omit=dev, plus a tool like Socket, Snyk, or your own SCA on every PR. Trend the number of new transitive dependencies over time. A sudden spike is a signal.For each affected client we ran the same playbook: snapshot every machine that had run a recent npm install, look at outbound network logs for unusual hosts, rotate every credential that lived on those machines, and rebuild from a clean lockfile that pre-dated the bad version. The clients who already had this list as a runbook were done in hours. Those who did not took weeks.
If you want us to run this drill against your own build pipeline, the contact form is two scrolls away. Twenty minutes of conversation usually saves a long weekend later.
We pen-test a lot of mobile apps. Different industries, different stacks—but the same ten findings show up almost every time. Here they are in plain English, with the one-line fix beside each.
None of these require exotic tooling to spot. A few hours with a proxy, a rooted test device, and a careful eye is enough. Fixing them takes a week. Ignoring them is what keeps incident response teams in business.
Most of the cloud incidents we are called into are not the result of advanced attackers. They are misconfigurations: a bucket that was set to public for a one-time test and never closed, an IAM role with * on actions because someone wanted the demo to "just work", a forgotten lambda with a credential printed in plaintext.
public-read or open bucket policies."*" on Action or Resource. If there are more than five, you have homework.AssumeRole calls from unexpected principals in the last 30 days.Cloud security is mostly hygiene. The teams that do well are the ones that schedule the boring review—not the ones with the fanciest tools.
RAG systems introduce a second supply chain: the document corpus. If the corpus is untrusted or easily poisoned, an attacker can insert instructions that override your system prompt and trigger unsafe actions. This is not a theoretical edge case; we see it in customer deployments across internal wikis, PDFs, and shared knowledge bases.
What changes in RAG? The model now treats retrieved content as authoritative context. Without strict boundaries, it will follow malicious instructions hidden inside trusted documents.
We recommend treating every retrieved document as untrusted input, even if it came from “internal” sources. Attackers only need one weak link — a stale document, an unreviewed upload, or a compromised wiki page — to poison the context.
Most teams already do some of this, but the key is consistency. Make guardrails part of the RAG pipeline, not an afterthought in the UI layer.
Agentic systems amplify risk because a single prompt can trigger multiple tool calls. When tools are overly permissive, the model can be tricked into taking real-world actions such as reading sensitive files, making unintended API calls, or leaking data through indirect channels.
We’ve seen successful prompt injection attacks where the model was tricked into “helpfully” exporting data, granting extra permissions, or executing actions outside of the user’s intent.
Well-designed guardrails reduce the attack surface without sacrificing the workflow benefits of agentic systems. The goal is not to block agents — it’s to ensure every action is accountable and intentional.
LLM systems often collect telemetry for observability. The problem: prompt and completion logs can accidentally store secrets, credentials, or sensitive business data. Once it hits a log or a trace, it’s very difficult to control downstream exposure.
We’ve seen incidents where secrets were leaked into monitoring dashboards, customer support tools, or long-term storage simply because logs were never scrubbed.
Security and observability can coexist, but only with strict data boundaries and enforcement. Treat LLM logs like sensitive production data — because they usually are.
We are an offensive security research studio dedicated to breaking technologies before adversaries do.
Most security reports are long, jargon-filled, and hard to act on. We do it differently.
We look at your business through an attacker’s eyes, then explain what we find in plain English—what’s broken, how bad it is, and exactly what to fix first. Deep expertise underneath, friendly conversation on top.
We saw too many companies passing audits while remaining fundamentally insecure. Pentesting had become a commodity—a race to the bottom focused on generating PDF reports rather than finding critical risks.
As the world moved to AI, LLMs, and IoT, traditional security firms struggled to keep up. They lacked the specialized research capabilities needed to test these new attack surfaces effectively.
FortySecurity was founded by a team of experienced security researchers to fill this void. We built a firm where research drives testing, and every engagement is treated as a potential zero-day discovery.
These principles guide every assessment we conduct and every report we write.
We don't test for compliance; we test for exploitability. We emulate motivated attackers who don't follow rules or scope documents.
We invest heavily in vulnerability research. Finding zero-days in vendor software is part of our DNA, not an afterthought.
No inflated risks or hidden findings. We tell you exactly what matters, why it matters, and how to fix it—plain and simple.
We aren't just vendors; we are extensions of your security team. We work with your developers to ensure fixes actually work.
Our team members are active contributors to the global security community. We don't just use tools; we build them and find the vulnerabilities they miss.
A team of bug bounty hunters and penetration testers acknowledged by world-class security teams, serving critical industries across India and beyond.
A few of the organizations across India and the Middle East who count on FortySecurity to keep their products, platforms, and people safe.
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No sales script, no jargon. Share a little about your team and what worries you most—we’ll suggest the right starting point in plain language.
sales@fortysecurity.com
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By appointment, Mon–FriA 20-minute call to understand your environment, timelines, and concerns. No commitment.
We write up a short proposal—what we’ll test, how long it takes, and what it costs. Fixed price, no surprises.
We run the assessment, walk you through the findings, and stay around to help your engineers ship the fixes.
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