Hunt a handle
Handle reuse is the cheapest strong link in OSINT: one string, checked in minutes, potentially tying a dozen platforms to one person. It is also the most over-trusted. Enumerators do not verify identity — they perform HTTP existence checks — and a hit list is a list of candidates, nothing more. The mistake that ruins these investigations is pasting the tool's output into the report. Enumeration is the cheap half; confirmation is the work.
Step 1 — Authorized scope
Read ../../ETHICS.md and write down, before any query: subject, objective, in-bounds selectors, out-of-bounds actions (logging in, contacting, requesting follows), and the governing jurisdiction. Handle hunting drifts easily — one run hands you thirty new platforms, and it is trivial to end up profiling an uninvolved person who shares the string.
Done when scope is written down and you can name what would put you out of bounds.
Step 2 — Pick your enumerator
maigret is the higher-value tool for correlation because it returns fields, not booleans. A display name, avatar URL, self-declared location, numeric user ID and an "also known as" list give you material to test the next platform against. Sherlock gives you a URL and a claim.
WhatsMyName is a detection list, not a scanner: a JSON file of site entries, each with a URI template and explicit match criteria (an expected HTTP status and an expected string in the body, plus the equivalent for "missing"). Read the entry for any site you doubt — it tells you exactly what the tool considered proof. Many wrappers and web front-ends consume the same list, so a hit in three different tools is often one rule firing three times, not three independent confirmations.
Done when every candidate is recorded with platform, URL, the tool that found it, and live/dead status.
Step 3 — Generate variants
The handle you were given is one point in a person's naming habit. Recover the habit and you find the accounts the first sweep missed.
- Separator swaps:
john.doe,john_doe,john-doe,johndoe - Truncations and initials:
jdoe,johnd,j_doe,doej - Number suffixes: birth year, birth year two-digit,
1,99,007 - Leetspeak and character substitution:
j0hnd0e,johnd0e - Email local part as handle, and handle as email local part
- Gamer-tag morphology: prefixes,
xX…Xx, clan tags, doubled letters
Full pattern list: reference/variant-patterns.md [blocked].
Two inference directions matter. Handle → name: jdoe_92 suggests a
first-initial-lastname pattern and a 1992 birth year, which is a hypothesis to
test, not a finding. Name → handle: if you already have a real name, generate
the handles that name would plausibly produce and enumerate those too — it often
outperforms starting from a handle someone gave you.
Done when the variant set is enumerated and the ones that produced hits are folded back into Step 2.
Step 4 — Confirm, or reject
For each candidate, look for evidence that survives a skeptical reader.
Strong:
- Same avatar. Verify with
find-the-original-image— a match to a stock photo or a third party's picture is a rejection, not a confirmation. - Byte-identical or near-identical bio text, especially with a typo or an unusual phrasing carried across.
- A self-declared cross-link: the profile links the other profile. Best evidence available short of an admission.
- A contact selector present on both (same email, same personal domain).
Moderate:
- Account creation dates clustering in a narrow window across platforms — people sign up for things in bursts.
- Follower/following overlap with the same distinctive small accounts.
- Writing style: idiom, punctuation habits, timezone of posting.
Weak on its own: the handle matching. That is the thing you are testing, not evidence for it.
Platforms exposing a numeric user ID are disproportionately useful. Where
IDs are issued in registration order, the ID bounds an account's creation date
even when the profile hides it. GitHub's
https://api.github.com/users/<login> returns a numeric id and created_at;
Discord's snowflake IDs encode a creation timestamp directly. Per-platform
detail: reference/platform-leakage.md [blocked].
Done when every candidate is graded confirmed, probable, or rejected, each with its evidence written next to it.
Where this goes wrong
Existence checks are HTTP heuristics. Every one of these produces a false positive:
- Soft 404s. The site returns 200 with a "user not found" page. If the match rule keys on status code, everything exists.
- Catch-all profile pages. Some platforms render a generic shell for any string and only 404 on the API.
- Rate-limit and CAPTCHA interstitials. A challenge page is a 200 with body content, so it can satisfy both the "found" and "missing" rules — and once you are rate-limited, results for the rest of the run are garbage. Re-run failures separately rather than trusting a single sweep.
- Reserved, squatted, and impersonation accounts. Registered, real, not your subject.
- Stale entries. Sites change their 404 behaviour and detection lists lag. Absence of a hit is not absence of an account.
The deeper problem is collision. Common handles belong to many unrelated people,
and a short or dictionary-word handle across ten platforms is ten people far
more often than one. Confidence should scale with the handle's distinctiveness:
a rare invented string is itself weak-to-moderate evidence, mike is none.
Do not resolve ambiguity by logging in, messaging, or requesting a follow. That
is interaction, out of scope by default, and it tells the subject you exist —
see investigate-without-getting-made.
Confidence grading
- Confirmed — an avatar match verified through
find-the-original-imageplus one other strong item, or a self-declared cross-link between the two profiles, or a shared contact selector. - Probable — distinctive handle plus one moderate item (creation-date cluster, follower overlap, consistent style) and no contradicting evidence.
- Unconfirmed — the handle matches and nothing else does. Report it as an enumeration hit, not as the subject's account.
- Rejected — content, language, timeline, or avatar provenance contradicts the subject. Record rejections; they stop the next analyst redoing the work.
Worked example
Given sunfish_ada. Sherlock returns 14 hits. maigret returns 9 with content,
including a code-hosting profile with display name "A. Okonkwo", a photography
site with the same avatar, and a forum with an empty shell profile.
The forum hit is discarded first: fetching a deliberately absurd handle on the same forum also returns 200 with an identical empty page. Catch-all, not an account.
The avatar on the photography site reverse-searches (via
find-the-original-image) to the same image on the code-hosting profile and
nowhere else — good. The code-hosting API gives a numeric ID and a creation date
in the same month as the photography account's stated join date. Two moderate
items plus an avatar match: confirmed for both.
A microblog hit with the same handle posts in a different language about unrelated subjects, on an account predating the others by six years. Different person, same string — rejected, and stated explicitly, because it is the first thing a reviewer will find.
Pivots
Legal and ToS notes
Automated enumeration hits platforms with scripted requests, which most terms of service prohibit regardless of the data being public. Keep concurrency low, do not defeat CAPTCHAs, and stop when a platform signals refusal. In the EU and UK, assembling scattered public accounts into a profile of a living person is processing personal data and needs a lawful basis and data minimisation.
Step 5 — Report
Run write-the-intel-brief. Give the platform/URL/confidence/evidence table,
list rejections with reasons, and lead with the real-name and contact selectors
the handles produced.
Done when every candidate in the table carries a grade and a source, and no enumeration hit appears without one.
