w=300&h=174" data-large-file="https://u2tech.files.wordpress.com/2010/03/seqonly.jpg? w=595" class="size-medium wp-image-169 " title="Sequential Timings Only" src="https://u2tech.files.wordpress.com/2010/03/seqonly.jpg? The problem with this is, if an uncontrolled (eg, external) entity has control over the number of items in the dynamic array, you could be vulnerable to a Denial of Service attack. Essentially when doing an operation like “CRT STRING” it has to scan the string character by character counting attribute, multi-value and sub-value marks as it does.
w=300&h=174" alt="" srcset="https://u2tech.files.wordpress.com/2010/03/seqonly.jpg? w=300&h=174 300w, https://u2tech.files.wordpress.com/2010/03/seqonly.jpg? w=600&h=348 600w, https://u2tech.files.wordpress.com/2010/03/seqonly.jpg? w=150&h=87 150w" sizes="(max-width: 300px) 100vw, 300px" A graph of sequential and chosen key timings " data-medium-file="https://u2tech.files.wordpress.com/2010/03/seqandchosen.jpg? “Well, that’s not nearly as good as yesterday, but you’re still a fast worker. The next day Schlemiel paints 30 yards of the road. If you increment Y or Z (or X in Uni Data’s case) and do the same operation, it has to re-scan the string from the start all over again.
The test is repeated for different key counts from 1000 to 59000 in 1000 increments. In fact, a public article on Pick Wiki pointed this out quite some time ago.
This resulting in the monitoring program saturating a CPU core. Place it in attribute 1, build a D-type dictionary and index it if you need, but not use it as the @ID!If you develop for a U2 system where you cannot afford for malicious internal/external entities to adversely affect system performance, then I highly suggest you read the above linked paper. Hash file vulnerability Dynamic Array vulnerability Suggestions The first place I’ll draw your attention to is the humble hash file at the core of Uni Data and Uni Verse.As you probably know, each record is placed in a group dependant on the hash value of its record ID, along with the modulo and hashing algorithm of the file.Knowing that they used Uni Data on the backend from his Interview (and their job ads), he installed Uni Data and makes some initial guesses at the modulo for their ‘users’ tables and calculates a few usernames sets for different modulus.Now, by going to their website and taking timings for the “Check username availability” feature, Harry was able to become reasonably sure of the modulo for the file.Essentially, he has taken the non-matching lookup performance of the hash file from O(1 k/n) to O(k) (where k is the number of keys and n is the modulo).Even worse than that, because of how level 1 overflows work, it now requires multiple disk reads as well (Uni Data only I believe).On the first day he takes a can of paint out to the road and finishes 300 yards of the road. The first program was a record lock monitoring program.It used GETREADU() Uni Basic command, after which it looped over every entry and generated a report on all locks over 10 minutes old. Basically, it read each record in a large file, locked it then if certain complex conditions were met, it updated an attribute and moved on to the next record. It didn’t release a record if it didn’t need updating. One that is less easy to bring to its knees by malicious users and unfortunate timings of buggy code?The next day he runs a script to sign-up all the usernames gradually over the day.After they have all been signed up, Harry now simply scripts a few “Check username availability” calls for his last username generated to start his Denial of Service attack.