- Using PBKDF2 properly: https://crackstation.net/hashing-security.htm
- Remove relation between users and passwords table: http://opine.me/a-better-way-to-store-password-hashes/
- Reduce risk of manipulation and enable password reset: http://www.opine.me/all-your-hashes-arent-belong-to-us/
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| --- ext/bigdecimal/bigdecimal.c.orig 2024-09-25 16:24:50 | |
| +++ ext/bigdecimal/bigdecimal.c 2024-09-25 16:25:15 | |
| @@ -65,7 +65,7 @@ | |
| static ID id_half; | |
| /* MACRO's to guard objects from GC by keeping them in stack */ | |
| -#define ENTER(n) volatile VALUE RB_UNUSED_VAR(vStack[n]);int iStack=0 | |
| +#define ENTER(n) volatile VALUE vStack[n];int iStack=0 | |
| #define PUSH(x) (vStack[iStack++] = (VALUE)(x)) | |
| #define SAVE(p) PUSH((p)->obj) |
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| class CreateNodes < ActiveRecord::Migration[6.0] | |
| def change | |
| create_table :nodes do |t| | |
| end | |
| create_table :node_edges do |t| | |
| t.integer :parent_id, null: false | |
| t.integer :child_id, null: false | |
| end | |
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| #!/usr/bin/python | |
| import sys | |
| import argparse, json, base64, struct | |
| import urllib2 | |
| from datetime import datetime | |
| LOGS = { | |
| 'icarus': 'https://ct.googleapis.com/icarus', | |
| 'pilot': 'https://ct.googleapis.com/pilot', |
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| #!/bin/bash -e | |
| DIR=$PWD/work | |
| mkdir -p ${DIR} | |
| rm -f ${DIR}/*.tar.gz | |
| LIBRESSL=libressl-2.4.5 | |
| HAPROXY=haproxy-1.7.5 | |
| PCRE=pcre-8.39 |
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| #!/usr/bin/python | |
| # Quick and dirty demonstration of CVE-2014-0160 by Jared Stafford (jspenguin@jspenguin.org) | |
| # The author disclaims copyright to this source code. | |
| # | |
| # -shirk added TLS version | |
| # -jpicht added SMTP STARTTLS hack | |
| import sys | |
| import struct |
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| // easing functions http://goo.gl/5HLl8 | |
| Math.easeInOutQuad = function (t, b, c, d) { | |
| t /= d/2; | |
| if (t < 1) { | |
| return c/2*t*t + b | |
| } | |
| t--; | |
| return -c/2 * (t*(t-2) - 1) + b; | |
| }; |
Operation: Decouple whisper from graphite.
Method: Create a graphite function that does a date histogram facet query against elasticsearch for a given query string for the time period viewed in the current graph.
Reason: graphite has some awesome math functions. Wouldn't it be cool if we could use those on logstash results?
The screenshot below is using logstash to watch the twitter stream of keywords "iphone" "apple" and "samsung" - then I graph them each, so we get an idea of popularity. As a bonus, I also do a movingAverage() on the iphone curve to show you why this is awesome.
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