Skip to main content

// capture the flag

· from $20/mo

An uncensored AI
for CTF challenges.

CTFs are time-boxed pattern matching.

The teams that win are the ones that recognise the trick fastest, write the solve script fastest, and avoid wasting an hour on plumbing that any senior team has automated. The major coding assistants will help with CTFs — until your prompt mentions exploit, payload, shellcode, or any other word that triggers their content policy. Then you spend half the round arguing with the tool. TartarusAI handles the parts that drain the clock — disassembly reading, z3 harness writing, payload encoding, RSA edge-case math, custom-cipher reversal — so you spend the round on the actual trick instead of the plumbing. Same enterprise-grade runtime safety guards. No content-policy refusal on legitimate CTF work. Same trust model as pwntools or any other CTF-specific tool: the work is professional sport, the tool just helps you win.

  • Zero refusals on offsec work
  • Custom-tuned model — not a wrapper
  • Runtime guards on by default
  • 256K context, sub-2s TTFT

refund if it ever refuses · no card on file · crypto-only · cancel any time

CTF round · live live
❯ this binary is asking for a password, here's the disasm — find the check
   target: ctf challenge, pwn category
  ▎▣ analyzed disasm: 84 functions
  ▎+ identified strcmp at 0x40128a checking against "r3v_b1n_4_w1n"
  ▎+ wrote solve.py (z3 not needed — direct compare)
  ▎$ python solve.py   ✓ flag captured
done.
256K context · sub-2s TTFT · MoE 30B / 3B-active

// what it does

What you ship
when nothing refuses.

Pwn — exploit primitives + ROP

Read the disasm, identify the bug class (BOF, format string, UAF, OOB write, off-by-one), write the leak, build the ROP chain, hand you the working exploit. libc fingerprinting, one-gadget hunting, heap massage scripts, custom heap-allocator analysis (tcache, fastbin, smallbin, unsorted bin), tcache poisoning, fastbin attack, large-bin attack.

Reverse — decompilation triage

Paste Ghidra / IDA pseudocode, get the algorithm port. Anti-debug bypass, custom-VM reversal, packer unpacking, custom crypto reversal, virtualised obfuscator analysis, Z3 harness writing for constraint satisfaction. The agent does the algorithm, you grab the flag.

Crypto — math you forgot

RSA edge cases (small e, common modulus, Wiener attack, Coppersmith, Hastad broadcast, padding-oracle), AES misuse (ECB, CTR-reuse, IV reuse, GCM nonce reuse), elliptic-curve quirks (invalid-curve attack, weak-curve attack, ECDSA nonce reuse), custom-cipher reversal. The agent recognises the textbook attack and writes the SageMath / Python solver.

Web + forensics

SQLi / SSTI / SSRF chains, JWT abuse, prototype-pollution PoCs, padding-oracle harnesses, packet-capture triage, memory-image analysis with Volatility, stego pipelines, image / audio forensics. Standard CTF surface, accelerated by an order of magnitude.

Misc / OSINT / hardware

OSINT pipelines for "find this person from these clues" challenges, hardware reverse engineering for embedded CTFs (UART log analysis, SPI flash dumps, custom-protocol decoding), bus protocol analysis, firmware unpacking. Particularly useful for the categories where the boilerplate is harder than the actual challenge.

Solve script + writeup automation

Once you have the flag, the agent ghostwrites the writeup — challenge description, solve approach, working solve script, key insight that made it click. Useful for team writeups that get published after the CTF, or for personal notes that turn into next-CTF preparation.

// workflow

A typical CTF round

You open the challenge, you read the description, you download the binary or the source. You drop the relevant context into the agent (disasm, source code, packet capture, memory image, stego challenge image) and ask for the read. The agent recognises the bug class or the trick within seconds — much faster than the human eye on the same disasm — and proposes the solve direction.

From there the loop is: you sanity-check the proposed direction, the agent writes the solve script, the verification gate runs it (locally if the challenge allows, against your own copy of the challenge if it does not), you tweak until the flag drops. For the ~80% of CTF challenges where the trick is "recognise the textbook pattern + write the boring solve script," the agent is sometimes 5-10x faster than a human team member doing the same work by hand.

For the ~20% of challenges where the trick is genuinely novel and requires creative human leaps, the agent is the senior teammate sitting next to you — proposing harnesses, sanity-checking your hypothesis, writing the parts of the solve that need to exist anyway. You stay in the creative loop; the agent does the typing.

// where it fits

In your existing CTF toolkit

TartarusAI does not replace pwntools, gdb / pwndbg / gef, IDA / Ghidra / Binary Ninja / radare2, angr, z3, SageMath, Volatility, Wireshark, Burp, or your team CTF framework. It writes the scripts that drive them. Custom pwntools harnesses, custom angr exploration scripts, z3 / SageMath solvers for crypto, Volatility plugins for forensics, Burp extensions for web challenges.

For team play, the agent integrates well with shared note-taking and challenge-tracking platforms. The solve script + writeup output drops straight into your team CTF wiki without further editing.

  • Pairs with pwntools, gdb / pwndbg / gef, IDA / Ghidra / Binary Ninja / radare2, angr, z3, SageMath, Volatility, Wireshark, Burp.
  • Generates pwntools harnesses, angr exploration scripts, z3 / SageMath solvers, Volatility plugins, Burp extensions.
  • Outputs are raw solve scripts you commit to your team CTF repo — no SaaS lock-in, integrates with your existing wiki / note-taking.

// rules

On using AI in competitive CTFs

CTF rules on AI assistance vary widely. Most jeopardy-style competitions allow any tool you can run locally; strict competitions (DEF CON CTF qualifiers and similar elite events) sometimes ban LLMs explicitly or implicitly. Read the rules of the specific CTF before using TartarusAI in a scored round.

For the much larger universe of casual / practice / training CTFs, attack-defense competitions, internal corporate CTFs, and post-CTF review work, no one cares — the value is the learning and the practice, not the integrity of a contested leaderboard. TartarusAI is particularly useful for that universe: post-CTF writeups, training new team members, building team-wide solve-script libraries, practising for upcoming competitions.

For high-integrity competitive play, our recommendation is to read the rules carefully, ask the organisers if the rules are ambiguous, and err on the side of not using TartarusAI mid-round if you are unsure. We would rather you not use the tool than misuse it.

// guards verification gate· read-before-overwrite· loop guard· failed-path blacklist· moderation off

// questions

What people actually ask.

Will it solve challenges for me end-to-end?+
It does the boilerplate (disasm reading, harness writing, payload encoding) and proposes the exploit chain. You are still the one who recognises the trick and decides which approach to commit to. Saves 30-60 minutes per challenge once you are used to the workflow.
Is using AI in CTFs against the rules?+
Depends on the CTF. Most jeopardy-style competitions allow any tool you can run locally; strict competitions (DEF CON CTF qualifiers, etc.) sometimes ban LLMs. Check the rules. For practice / non-competitive solving, no one cares.
Does it know common CTF patterns?+
Yes — the model is tuned on offensive-security and adversarial-code workflows. Recognizes RSA-CRT fault, BLS12-381 quirks, FSB primitives, classic heap shaping recipes, common reversing tricks. Faster than grepping CTF writeups.
Can I use it during a live CTF without leaking the challenge?+
We do not train on prompts and sessions auto-purge in 24h. Some CTFs forbid sending challenge data to third-party services — read the rules. For team practice and post-CTF review, no concern.
How is it on the harder pwn categories (heap, kernel)?+
Strong on heap (tcache poisoning, fastbin attack, large-bin attack, House of Force, House of Orange, etc.) and competent on kernel pwn (SMEP/SMAP/KASLR bypass research, slab-spray construction). For the most-difficult kernel pwn categories the model is helpful but not always sufficient on its own — pair with your own kernel-pwn experience.
Does it know the SageMath / z3 / Coppersmith ecosystem for crypto challenges?+
Yes. The agent writes SageMath solvers for elliptic curve attacks, Coppersmith harnesses for partial-key recovery, z3 constraint problems for "find input matching constraints" puzzles, custom solvers for unusual cipher constructions.
Can it help with hardware / embedded CTFs?+
Yes — UART log analysis, SPI flash dumps, custom-protocol decoding, JTAG / SWD interaction scripts, firmware unpacking. Particularly useful for the embedded category where the boilerplate (getting a shell on the device) is harder than the actual flag-finding step.
Will it help write the team writeup?+
Yes. After the round, paste your solve notes and the agent ghostwrites the writeup in standard CTF-writeup style — challenge description, observation, exploitation, solve script, key insight. Useful for teams that publish writeups after the event.

// ready

Stop fighting refusals.
Start shipping the engagement.

One tier covers most engagements at $20/month. If the agent ever refuses, hedges, or returns neutered output on legitimate engagement work, we refund — see the refund policy.

refund if it ever refuses · no card on file · crypto-only