Early access. The directory is still filling out, and every rating here comes from a researcher's reported experience.

In brief. Affirm is a bug bounty program on HackerOne. It received 64 reports in the 90 days to November 8, 2026, about 8 per in-scope asset. As of Nov 8, 2026. Markdown for agents

NR Unrated

Affirm

Affirm HackerOne
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Found a vulnerability?

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Reports are private. The report body is encrypted at rest. BugRater holds the key, so the analyst handling your report can read it, and we log every time someone does.

Program metrics HackerOne, published

These are HackerOne’s own figures for this program, taken from its public page. Researchers did not report them, and they don't count toward the BugRater grade. Captured 8 Nov 2026.

What it pays, by severity

Critical amount not published 2 reports
High $2,498 avg 19 reports indicative
Medium $660 avg 55 reports firm
Low $300 avg 26 reports firm

$100,565 paid to researchers in total, $23,183 of it in the last 90 days. This is HackerOne’s lifetime figure. It shows the program has paid out before. It doesn't tell you what any one report will get.

Intake & responsiveness, last 90 days

Reports received
64
in 90 days
Resolved
115
all time, last one 16 days ago
Participants
142
hunters engaged
Response efficiency
85%
meeting its targets, HackerOne’s figure
SLA misses
0
targets missed
Reports received, day by day, last 30 days 50–64
9 Oct 64 reports 8 Nov

Response targets it sets itself

First response
2 days
Triage
10 days
Bounty
30 days
Resolution
30 days

These are targets the program set. They don't show whether it meets them.

Barriers to submitting

Open to submit. HackerOne lists no requirements for submitting a report here.

Over 78 days (192 snapshots): intake up 5 reports; response efficiency up 10 points; 90-day payout up $5,254.

See how this program’s report load compares to others

Reviews

0 published

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Who this program credits

145 credited

Researchers HackerOne shows on this program’s public thanks list, best position first. “Recognised” is how many of a hunter’s submissions the program accepted; the ratio is their signal here, not our judgement of them.

# Researcher Reputation Recognised / submitted
1 ganeshbagaria 361 11 / 15 73%
2 no_01 334 5 / 5 100%
3 nightmaresthereallol 178 2 / 4 50%
4 pesticide 146 3 / 4 75%
5 n1had 118 4 / 12 33%
6 astrounder 114 2 / 4 50%
6 uiltonlopes 114 0 / 0
8 yogesh_ojha 94 2 / 4 50%
9 pungente 89 2 / 2 100%
9 gujjuboy10x00 22 1 / 3 33%
10 mikey96 86 3 / 3 100%
11 godiego 68 4 / 7 57%
12 1sequalt0 64 2 / 14 14%
13 obi 61 3 / 4 75%
14 bsysop 57 1 / 3 33%
14 deeevv 57 1 / 4 25%
14 kaiksi 57 0 / 0
14 mason0x01 57 1 / 1 100%
14 morwnbrgr 57 1 / 1 100%
14 petrescu 57 1 / 1 100%
20 insiderinvests 54 2 / 10 20%
20 unnamedx 32 1 / 1 100%
20 kushagra 22 1 / 1 100%
21 bugfix22 50 0 / 0
22 jakehhunter 46 3 / 4 75%

Showing the top 25 of 145 credited on HackerOne.

Program profile HackerOne, imported

HackerOne published these facts on the program's page. Researchers did not report them, and they don't count toward the BugRater grade. Last checked 6 Nov 2026.

Responsiveness
86% HackerOne’s figure
Swag
No
Currency
USD
Submissions
Open
Launched
Aug 2020
Scope entries
16 HackerOne’s count

Scope

15 assets
AssetTypeEligibilityMax severity
com.affirm.central.audit GOOGLE PLAY APP ID ✓ bounty Critical
com.affirm.internal.hackerone APPLE STORE APP ID ✓ bounty Critical
hackerone.affirm-odin.com URL ✓ bounty Critical
helpcenter.affirm.ca URL ✓ bounty Critical
helpcenter.affirm.com URL ✓ bounty Critical
Show all 15 assets
AssetTypeEligibilityMax severity
sandbox.affirm.com URL ✓ bounty Critical
*.affirm.com WILDCARD out None
*.return.ly WILDCARD out None
*.returnly.com WILDCARD out None
dashboard.dev.return.ly URL out None
dashboard.returnly.com URL out None
direct-hackerone.affirm-odin.com URL submit only None
test-store-subdomain.dev.return.ly URL out None
test-store-subdomain.returnly.com URL out None
vcn-hackerone.affirm-odin.com URL submit only None

HackerOne lists 16 scope entries. Its public listing groups many assets under one label, so we show identical entries once.